diff --git "a/H100_llama8b_pp1_tp1/profiling_bs1_pl4096.json" "b/H100_llama8b_pp1_tp1/profiling_bs1_pl4096.json"
deleted file mode 100644--- "a/H100_llama8b_pp1_tp1/profiling_bs1_pl4096.json"
+++ /dev/null
@@ -1,18548 +0,0 @@
-{
-  "context": {
-    "python_version": "3.12.9 | packaged by Anaconda, Inc. | (main, Feb  6 2025, 18:56:27) [GCC 11.2.0]",
-    "torch_version": "2.5.1+cu124",
-    "engine_args": {
-      "model": "deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
-      "served_model_name": null,
-      "tokenizer": "deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
-      "task": "auto",
-      "skip_tokenizer_init": false,
-      "tokenizer_mode": "auto",
-      "trust_remote_code": false,
-      "allowed_local_media_path": null,
-      "download_dir": null,
-      "load_format": "dummy",
-      "config_format": "auto",
-      "dtype": "auto",
-      "kv_cache_dtype": "auto",
-      "seed": 0,
-      "max_model_len": null,
-      "distributed_executor_backend": null,
-      "pipeline_parallel_size": 1,
-      "tensor_parallel_size": 1,
-      "max_parallel_loading_workers": null,
-      "block_size": null,
-      "enable_prefix_caching": false,
-      "disable_sliding_window": false,
-      "use_v2_block_manager": true,
-      "swap_space": 4,
-      "cpu_offload_gb": 0,
-      "gpu_memory_utilization": 0.9,
-      "max_num_batched_tokens": 8000,
-      "max_num_partial_prefills": 1,
-      "max_long_partial_prefills": 1,
-      "long_prefill_token_threshold": 0,
-      "max_num_seqs": 256,
-      "max_logprobs": 20,
-      "disable_log_stats": false,
-      "revision": null,
-      "code_revision": null,
-      "rope_scaling": null,
-      "rope_theta": null,
-      "hf_overrides": null,
-      "tokenizer_revision": null,
-      "quantization": null,
-      "enforce_eager": true,
-      "max_seq_len_to_capture": 8192,
-      "disable_custom_all_reduce": false,
-      "tokenizer_pool_size": 0,
-      "tokenizer_pool_type": "ray",
-      "tokenizer_pool_extra_config": null,
-      "limit_mm_per_prompt": null,
-      "mm_processor_kwargs": null,
-      "disable_mm_preprocessor_cache": false,
-      "enable_lora": false,
-      "enable_lora_bias": false,
-      "max_loras": 1,
-      "max_lora_rank": 16,
-      "enable_prompt_adapter": false,
-      "max_prompt_adapters": 1,
-      "max_prompt_adapter_token": 0,
-      "fully_sharded_loras": false,
-      "lora_extra_vocab_size": 256,
-      "long_lora_scaling_factors": null,
-      "lora_dtype": "auto",
-      "max_cpu_loras": null,
-      "device": "auto",
-      "num_scheduler_steps": 1,
-      "multi_step_stream_outputs": true,
-      "ray_workers_use_nsight": false,
-      "num_gpu_blocks_override": null,
-      "num_lookahead_slots": 0,
-      "model_loader_extra_config": null,
-      "ignore_patterns": [],
-      "preemption_mode": null,
-      "scheduler_delay_factor": 0.0,
-      "enable_chunked_prefill": null,
-      "guided_decoding_backend": "xgrammar",
-      "logits_processor_pattern": null,
-      "speculative_model": null,
-      "speculative_model_quantization": null,
-      "speculative_draft_tensor_parallel_size": null,
-      "num_speculative_tokens": null,
-      "speculative_disable_mqa_scorer": false,
-      "speculative_max_model_len": null,
-      "speculative_disable_by_batch_size": null,
-      "ngram_prompt_lookup_max": null,
-      "ngram_prompt_lookup_min": null,
-      "spec_decoding_acceptance_method": "rejection_sampler",
-      "typical_acceptance_sampler_posterior_threshold": null,
-      "typical_acceptance_sampler_posterior_alpha": null,
-      "qlora_adapter_name_or_path": null,
-      "disable_logprobs_during_spec_decoding": null,
-      "otlp_traces_endpoint": null,
-      "collect_detailed_traces": null,
-      "disable_async_output_proc": false,
-      "scheduling_policy": "fcfs",
-      "scheduler_cls": "vllm.core.scheduler.Scheduler",
-      "override_neuron_config": null,
-      "override_pooler_config": null,
-      "compilation_config": null,
-      "worker_cls": "auto",
-      "kv_transfer_config": null,
-      "generation_config": null,
-      "override_generation_config": null,
-      "enable_sleep_mode": false,
-      "model_impl": "auto",
-      "calculate_kv_scales": false,
-      "additional_config": null
-    },
-    "prompt_len": 0,
-    "batch_size": 1,
-    "num_steps": 2,
-    "complete_num_requests_per_step": null,
-    "save_chrome_traces_folder": null
-  },
-  "prefill": {
-    "metadata": {
-      "num_running_seqs": null
-    },
-    "summary_stats": [
-      {
-        "entry": {
-          "name": "LlamaForCausalLM",
-          "cuda_time_us": 94699.17500000002,
-          "pct_cuda_time": 99.4739494416884,
-          "invocations": 1
-        },
-        "children": [
-          {
-            "entry": {
-              "name": "VocabParallelEmbedding(weight=bfloat16[128256, 4096])",
-              "cuda_time_us": 127.775,
-              "pct_cuda_time": 0.13421747222097483,
-              "invocations": 1
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "void at::native::(anonymous namespace)::indexSelectLargeIndex<c10::BFloat16, long, unsigned int, 2, 2, -2, true>(at::cuda::detail::TensorInfo<c10::BFloat16, unsigned int>, at::cuda::detail::TensorInfo<c10::BFloat16 const, unsigned int>, at::cuda::detail::TensorInfo<long const, unsigned int>, int, int, unsigned int, unsigned int, long)",
-                  "cuda_time_us": 127.775,
-                  "pct_cuda_time": 0.13421747222097483,
-                  "invocations": 1
-                },
-                "children": []
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cuda_time_us": 94525.993,
-              "pct_cuda_time": 99.29203552837066,
-              "invocations": 32
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cuda_time_us": 2845.9129999999996,
-                  "pct_cuda_time": 2.9894051967975823,
-                  "invocations": 64
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "void vllm::rms_norm_kernel<c10::BFloat16>(c10::BFloat16*, c10::BFloat16 const*, c10::BFloat16 const*, float, int, int)",
-                      "cuda_time_us": 71.264,
-                      "pct_cuda_time": 0.07485716251501115,
-                      "invocations": 1
-                    },
-                    "children": []
-                  },
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cuda_time_us": 2774.6489999999994,
-                      "pct_cuda_time": 2.9145480342825705,
-                      "invocations": 63
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cuda_time_us": 25478.952999999998,
-                  "pct_cuda_time": 26.763613120696718,
-                  "invocations": 32
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cuda_time_us": 8821.841,
-                      "pct_cuda_time": 9.2666421393493,
-                      "invocations": 32
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cuda_time_us": 29.729000000000013,
-                          "pct_cuda_time": 0.031227949377087554,
-                          "invocations": 32
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cuda_time_us": 8792.112000000001,
-                          "pct_cuda_time": 9.235414189972213,
-                          "invocations": 32
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cuda_time_us": 1748.3490000000002,
-                      "pct_cuda_time": 1.83650153269473,
-                      "invocations": 32
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cuda_time_us": 1748.3490000000002,
-                          "pct_cuda_time": 1.83650153269473,
-                          "invocations": 32
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cuda_time_us": 8695.786,
-                      "pct_cuda_time": 9.134231390291855,
-                      "invocations": 32
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cuda_time_us": 729.1479999999999,
-                          "pct_cuda_time": 0.7659119658382261,
-                          "invocations": 32
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cuda_time_us": 7918.416000000002,
-                          "pct_cuda_time": 8.317666049807261,
-                          "invocations": 32
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cuda_time_us": 48.22200000000001,
-                          "pct_cuda_time": 0.05065337464636939,
-                          "invocations": 32
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cuda_time_us": 6212.977,
-                      "pct_cuda_time": 6.526238058360834,
-                      "invocations": 32
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cuda_time_us": 31.231000000000012,
-                          "pct_cuda_time": 0.03280568088384477,
-                          "invocations": 32
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cuda_time_us": 6181.746000000001,
-                          "pct_cuda_time": 6.493432377476989,
-                          "invocations": 32
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cuda_time_us": 66201.12700000001,
-                  "pct_cuda_time": 69.53901721087637,
-                  "invocations": 32
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cuda_time_us": 41526.33599999999,
-                      "pct_cuda_time": 43.62011229519753,
-                      "invocations": 32
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cuda_time_us": 31.39000000000001,
-                          "pct_cuda_time": 0.03297269773442693,
-                          "invocations": 32
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cuda_time_us": 41494.94599999999,
-                          "pct_cuda_time": 43.58713959746311,
-                          "invocations": 32
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cuda_time_us": 5641.842000000001,
-                      "pct_cuda_time": 5.926306178126621,
-                      "invocations": 32
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cuda_time_us": 5641.842000000001,
-                          "pct_cuda_time": 5.926306178126621,
-                          "invocations": 32
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cuda_time_us": 19032.949,
-                      "pct_cuda_time": 19.992598737552186,
-                      "invocations": 32
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cuda_time_us": 32.254000000000005,
-                          "pct_cuda_time": 0.0338802609979677,
-                          "invocations": 32
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cuda_time_us": 19000.695000000003,
-                          "pct_cuda_time": 19.95871847655422,
-                          "invocations": 32
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "RMSNorm(weight=bfloat16[4096])",
-              "cuda_time_us": 45.407,
-              "pct_cuda_time": 0.04769644109675447,
-              "invocations": 1
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                  "cuda_time_us": 45.407,
-                  "pct_cuda_time": 0.04769644109675447,
-                  "invocations": 1
-                },
-                "children": []
-              }
-            ]
-          }
-        ]
-      },
-      {
-        "entry": {
-          "name": "LogitsProcessor",
-          "cuda_time_us": 356.608,
-          "pct_cuda_time": 0.3745883336629027,
-          "invocations": 1
-        },
-        "children": [
-          {
-            "entry": {
-              "name": "void at::native::(anonymous namespace)::indexSelectSmallIndex<c10::BFloat16, long, unsigned int, 2, 2, -2>(at::cuda::detail::TensorInfo<c10::BFloat16, unsigned int>, at::cuda::detail::TensorInfo<c10::BFloat16 const, unsigned int>, at::cuda::detail::TensorInfo<long const, unsigned int>, int, int, unsigned int, long)",
-              "cuda_time_us": 3.265,
-              "pct_cuda_time": 0.0034296227493757214,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memset (Device)",
-              "cuda_time_us": 0.768,
-              "pct_cuda_time": 0.0008067229009251313,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-              "cuda_time_us": 352.575,
-              "pct_cuda_time": 0.37035198801260183,
-              "invocations": 1
-            },
-            "children": []
-          }
-        ]
-      },
-      {
-        "entry": {
-          "name": "Sampler",
-          "cuda_time_us": 144.192,
-          "pct_cuda_time": 0.1514622246486934,
-          "invocations": 1
-        },
-        "children": [
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cuda_time_us": 16.544,
-              "pct_cuda_time": 0.017378155824095538,
-              "invocations": 7
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#7}::operator()() const::{lambda(float)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1> >(int, at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#7}::operator()() const::{lambda(float)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1>)",
-              "cuda_time_us": 4.704,
-              "pct_cuda_time": 0.0049411777681664295,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::elementwise_kernel<128, 4, at::native::gpu_kernel_impl<at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > >(at::TensorIteratorBase&, at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > const&)::{lambda(int)#1}>(int, at::native::gpu_kernel_impl<at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > >(at::TensorIteratorBase&, at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > const&)::{lambda(int)#1})",
-              "cuda_time_us": 5.376,
-              "pct_cuda_time": 0.00564706030647592,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::(anonymous namespace)::cunn_SoftMaxForward<4, float, float, float, at::native::(anonymous namespace)::SoftMaxForwardEpilogue>(float*, float const*, int)",
-              "cuda_time_us": 40.64,
-              "pct_cuda_time": 0.04268908684062153,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::(anonymous namespace)::cunn_SoftMaxForward<4, float, float, float, at::native::(anonymous namespace)::LogSoftMaxForwardEpilogue>(float*, float const*, int)",
-              "cuda_time_us": 32.576,
-              "pct_cuda_time": 0.034218496380907654,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#4}::operator()() const::{lambda(long)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1> >(int, at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#4}::operator()() const::{lambda(long)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1>)",
-              "cuda_time_us": 2.144,
-              "pct_cuda_time": 0.0022521014317493254,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::index_elementwise_kernel<128, 4, at::native::gpu_index_kernel<at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1}>(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>, at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1} const&)::{lambda(int)#1}>(long, at::native::gpu_index_kernel<at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1}>(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>, at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1} const&)::{lambda(int)#1})",
-              "cuda_time_us": 5.312,
-              "pct_cuda_time": 0.005579833398065492,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::reduce_kernel<512, 1, at::native::ReduceOp<float, at::native::ArgMaxOps<float>, unsigned int, long, 4> >(at::native::ReduceOp<float, at::native::ArgMaxOps<float>, unsigned int, long, 4>)",
-              "cuda_time_us": 33.728,
-              "pct_cuda_time": 0.03542858073229535,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy DtoH (Device -> Pageable)",
-              "cuda_time_us": 3.168,
-              "pct_cuda_time": 0.003327731966316167,
-              "invocations": 1
-            },
-            "children": []
-          }
-        ]
-      }
-    ],
-    "model_stats": [
-      {
-        "entry": {
-          "name": "LlamaForCausalLM",
-          "cpu_time_us": 17255.819,
-          "cuda_time_us": 94699.17500000002,
-          "pct_cuda_time": 99.4739494416884,
-          "trace": ""
-        },
-        "children": [
-          {
-            "entry": {
-              "name": "VocabParallelEmbedding(weight=bfloat16[128256, 4096])",
-              "cpu_time_us": 66.087,
-              "cuda_time_us": 127.775,
-              "pct_cuda_time": 0.13421747222097483,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "void at::native::(anonymous namespace)::indexSelectLargeIndex<c10::BFloat16, long, unsigned int, 2, 2, -2, true>(at::cuda::detail::TensorInfo<c10::BFloat16, unsigned int>, at::cuda::detail::TensorInfo<c10::BFloat16 const, unsigned int>, at::cuda::detail::TensorInfo<long const, unsigned int>, int, int, unsigned int, unsigned int, long)",
-                  "cpu_time_us": 0,
-                  "cuda_time_us": 127.775,
-                  "pct_cuda_time": 0.13421747222097483,
-                  "trace": "index_select(bfloat16[128256, 4096], 0, int64[4096]) <- embedding(bfloat16[128256, 4096], int64[4096], -1, False, False)"
-                },
-                "children": []
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 865.73,
-              "cuda_time_us": 3222.3269999999998,
-              "pct_cuda_time": 3.3847981577726247,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 48.726,
-                  "cuda_time_us": 71.264,
-                  "pct_cuda_time": 0.07485716251501115,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "void vllm::rms_norm_kernel<c10::BFloat16>(c10::BFloat16*, c10::BFloat16 const*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 71.264,
-                      "pct_cuda_time": 0.07485716251501115,
-                      "trace": "_C::rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 627.754,
-                  "cuda_time_us": 878.684,
-                  "pct_cuda_time": 0.9229876373391902,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 87.367,
-                      "cuda_time_us": 300.991,
-                      "pct_cuda_time": 0.31616709983379715,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 300.255,
-                          "pct_cuda_time": 0.3153939903870772,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 194.088,
-                      "cuda_time_us": 57.152,
-                      "pct_cuda_time": 0.060033629210511856,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 57.152,
-                          "pct_cuda_time": 0.060033629210511856,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 217.039,
-                      "cuda_time_us": 305.919,
-                      "pct_cuda_time": 0.32134357178140005,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.52,
-                          "pct_cuda_time": 0.02470588884083215,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 280.799,
-                          "pct_cuda_time": 0.29495701023030724,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.6,
-                          "pct_cuda_time": 0.0016806727102606906,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 73.253,
-                      "cuda_time_us": 214.622,
-                      "pct_cuda_time": 0.2254433365134812,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.735,
-                          "pct_cuda_time": 0.0007720590262760047,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 213.887,
-                          "pct_cuda_time": 0.22467127748720517,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 26.61,
-                  "cuda_time_us": 44.032,
-                  "pct_cuda_time": 0.046252112986374196,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.032,
-                      "pct_cuda_time": 0.046252112986374196,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 128.122,
-                  "cuda_time_us": 2228.3469999999998,
-                  "pct_cuda_time": 2.340701244932049,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 44.016,
-                      "cuda_time_us": 1419.037,
-                      "pct_cuda_time": 1.4905854754688745,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.768,
-                          "pct_cuda_time": 0.0008067229009251313,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1418.269,
-                          "pct_cuda_time": 1.4897787525679493,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 29.454,
-                      "cuda_time_us": 182.079,
-                      "pct_cuda_time": 0.19125950400722266,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 182.079,
-                          "pct_cuda_time": 0.19125950400722266,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 38.651,
-                      "cuda_time_us": 627.231,
-                      "pct_cuda_time": 0.658856265455952,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 626.495,
-                          "pct_cuda_time": 0.6580831560092321,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 582.613,
-              "cuda_time_us": 2951.322,
-              "pct_cuda_time": 3.100128965370001,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 18.859,
-                  "cuda_time_us": 44.0,
-                  "pct_cuda_time": 0.046218499532168986,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.0,
-                      "pct_cuda_time": 0.046218499532168986,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 421.202,
-                  "cuda_time_us": 815.1670000000001,
-                  "pct_cuda_time": 0.8562680820031728,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 35.504,
-                      "cuda_time_us": 278.975,
-                      "pct_cuda_time": 0.2930410433406101,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.024,
-                          "pct_cuda_time": 0.001075630534566842,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 277.951,
-                          "pct_cuda_time": 0.2919654128060432,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 125.134,
-                      "cuda_time_us": 54.977,
-                      "pct_cuda_time": 0.05774896474500123,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.977,
-                          "pct_cuda_time": 0.05774896474500123,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 178.446,
-                      "cuda_time_us": 282.68800000000005,
-                      "pct_cuda_time": 0.2969412544488588,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.648,
-                          "pct_cuda_time": 0.024840342657653003,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 257.696,
-                          "pct_cuda_time": 0.2706891467145868,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.344,
-                          "pct_cuda_time": 0.00141176507661898,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 46.477,
-                      "cuda_time_us": 198.52700000000002,
-                      "pct_cuda_time": 0.2085368194687026,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.12,
-                          "pct_cuda_time": 0.0011764708971824835,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 197.407,
-                          "pct_cuda_time": 0.20736034857152008,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 18.452,
-                  "cuda_time_us": 44.639,
-                  "pct_cuda_time": 0.04688971819582935,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.639,
-                      "pct_cuda_time": 0.04688971819582935,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 104.658,
-                  "cuda_time_us": 2047.516,
-                  "pct_cuda_time": 2.15075266563883,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 35.735,
-                      "cuda_time_us": 1292.1570000000002,
-                      "pct_cuda_time": 1.3573081295452019,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.344,
-                          "pct_cuda_time": 0.00141176507661898,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1290.813,
-                          "pct_cuda_time": 1.3558963644685829,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 23.348,
-                      "cuda_time_us": 174.304,
-                      "pct_cuda_time": 0.18309248505579961,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.304,
-                          "pct_cuda_time": 0.18309248505579961,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 33.55,
-                      "cuda_time_us": 581.055,
-                      "pct_cuda_time": 0.6103520510378283,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 580.319,
-                          "pct_cuda_time": 0.6095789415911084,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 523.093,
-              "cuda_time_us": 2890.967,
-              "pct_cuda_time": 3.0367308394776362,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.391,
-                  "cuda_time_us": 44.896,
-                  "pct_cuda_time": 0.047159676249914975,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.896,
-                      "pct_cuda_time": 0.047159676249914975,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 362.922,
-                  "cuda_time_us": 780.702,
-                  "pct_cuda_time": 0.8200653414037135,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 33.708,
-                      "cuda_time_us": 271.07099999999997,
-                      "pct_cuda_time": 0.28473852015192225,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.376,
-                          "pct_cuda_time": 0.0014453785308241936,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 269.695,
-                          "pct_cuda_time": 0.28329314162109803,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 104.264,
-                      "cuda_time_us": 54.016,
-                      "pct_cuda_time": 0.056739510698400906,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.016,
-                          "pct_cuda_time": 0.056739510698400906,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 154.065,
-                      "cuda_time_us": 266.527,
-                      "pct_cuda_time": 0.2799654096547819,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.4,
-                          "pct_cuda_time": 0.023529417943649662,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 242.559,
-                          "pct_cuda_time": 0.2547889324550768,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.568,
-                          "pct_cuda_time": 0.0016470592560554765,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 41.246,
-                      "cuda_time_us": 189.088,
-                      "pct_cuda_time": 0.1986219008986084,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.768,
-                          "pct_cuda_time": 0.0008067229009251313,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.32,
-                          "pct_cuda_time": 0.19781517799768322,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.057,
-                  "cuda_time_us": 43.328,
-                  "pct_cuda_time": 0.045512616993859493,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.328,
-                      "pct_cuda_time": 0.045512616993859493,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 99.961,
-                  "cuda_time_us": 2022.0410000000002,
-                  "pct_cuda_time": 2.123993204830148,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.337,
-                      "cuda_time_us": 1263.613,
-                      "pct_cuda_time": 1.3273249283941513,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.768,
-                          "pct_cuda_time": 0.0008067229009251313,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1262.845,
-                          "pct_cuda_time": 1.326518205493226,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 22.046,
-                      "cuda_time_us": 175.007,
-                      "pct_cuda_time": 0.1838309306278704,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 175.007,
-                          "pct_cuda_time": 0.1838309306278704,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 32.185,
-                      "cuda_time_us": 583.4209999999999,
-                      "pct_cuda_time": 0.6128373458081263,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.087,
-                          "pct_cuda_time": 0.0011418070225333564,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 582.334,
-                          "pct_cuda_time": 0.611695538785593,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 528.428,
-              "cuda_time_us": 2891.352,
-              "pct_cuda_time": 3.037135251348542,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.071,
-                  "cuda_time_us": 44.704,
-                  "pct_cuda_time": 0.04695799552468369,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.704,
-                      "pct_cuda_time": 0.04695799552468369,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 376.622,
-                  "cuda_time_us": 783.6759999999999,
-                  "pct_cuda_time": 0.8231892918039104,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 30.857,
-                      "cuda_time_us": 271.39099999999996,
-                      "pct_cuda_time": 0.28507465469397436,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 270.655,
-                          "pct_cuda_time": 0.28430154524725443,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 103.531,
-                      "cuda_time_us": 53.92,
-                      "pct_cuda_time": 0.05663867033578526,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 53.92,
-                          "pct_cuda_time": 0.05663867033578526,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 162.877,
-                      "cuda_time_us": 266.654,
-                      "pct_cuda_time": 0.28009881305115886,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.655,
-                          "pct_cuda_time": 0.023797275156847465,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 242.368,
-                          "pct_cuda_time": 0.2545883021502894,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.631,
-                          "pct_cuda_time": 0.0017132357440219914,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 47.676,
-                      "cuda_time_us": 191.711,
-                      "pct_cuda_time": 0.20137715372299203,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.728,
-                          "pct_cuda_time": 0.0018151265270815455,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 189.983,
-                          "pct_cuda_time": 0.19956202719591046,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 18.674,
-                  "cuda_time_us": 42.687,
-                  "pct_cuda_time": 0.04483929748931131,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 42.687,
-                      "pct_cuda_time": 0.04483929748931131,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 103.028,
-                  "cuda_time_us": 2020.285,
-                  "pct_cuda_time": 2.122148666530637,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 36.575,
-                      "cuda_time_us": 1262.622,
-                      "pct_cuda_time": 1.3262839617342335,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.768,
-                          "pct_cuda_time": 0.0008067229009251313,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1261.854,
-                          "pct_cuda_time": 1.3254772388333083,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.474,
-                      "cuda_time_us": 175.104,
-                      "pct_cuda_time": 0.18393282141092995,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 175.104,
-                          "pct_cuda_time": 0.18393282141092995,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 33.154,
-                      "cuda_time_us": 582.559,
-                      "pct_cuda_time": 0.6119318833854734,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.408,
-                          "pct_cuda_time": 0.0014789919850294075,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 581.151,
-                          "pct_cuda_time": 0.6104528914004439,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 531.975,
-              "cuda_time_us": 2886.232,
-              "pct_cuda_time": 3.0317570986757083,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.618,
-                  "cuda_time_us": 43.872,
-                  "pct_cuda_time": 0.04608404571534813,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.872,
-                      "pct_cuda_time": 0.04608404571534813,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 376.051,
-                  "cuda_time_us": 781.151,
-                  "pct_cuda_time": 0.8205369801830302,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 32.781,
-                      "cuda_time_us": 270.751,
-                      "pct_cuda_time": 0.2844023856098701,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.96,
-                          "pct_cuda_time": 0.0010084036261564142,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 269.791,
-                          "pct_cuda_time": 0.2833939819837137,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 104.423,
-                      "cuda_time_us": 54.048,
-                      "pct_cuda_time": 0.05677312415260612,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.048,
-                          "pct_cuda_time": 0.05677312415260612,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 161.396,
-                      "cuda_time_us": 266.848,
-                      "pct_cuda_time": 0.28030259461727797,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.368,
-                          "pct_cuda_time": 0.023495804489444452,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 242.816,
-                          "pct_cuda_time": 0.25505889050916236,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.664,
-                          "pct_cuda_time": 0.001747899618671118,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 44.869,
-                      "cuda_time_us": 189.504,
-                      "pct_cuda_time": 0.19905887580327616,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.768,
-                          "pct_cuda_time": 0.19828576635655626,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.506,
-                  "cuda_time_us": 43.455,
-                  "pct_cuda_time": 0.045646020390236436,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.455,
-                      "pct_cuda_time": 0.045646020390236436,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 100.487,
-                  "cuda_time_us": 2017.754,
-                  "pct_cuda_time": 2.119490052387093,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.687,
-                      "cuda_time_us": 1261.596,
-                      "pct_cuda_time": 1.3252062303587786,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.056,
-                          "pct_cuda_time": 0.0011092439887720558,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1260.54,
-                          "pct_cuda_time": 1.3240969863700067,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.84,
-                      "cuda_time_us": 174.815,
-                      "pct_cuda_time": 0.18362924990263912,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.815,
-                          "pct_cuda_time": 0.18362924990263912,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 34.023,
-                      "cuda_time_us": 581.343,
-                      "pct_cuda_time": 0.6106545721256753,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 580.607,
-                          "pct_cuda_time": 0.6098814626789554,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 523.021,
-              "cuda_time_us": 2889.978,
-              "pct_cuda_time": 3.035691973658606,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.966,
-                  "cuda_time_us": 43.776,
-                  "pct_cuda_time": 0.04598320535273249,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.776,
-                      "pct_cuda_time": 0.04598320535273249,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 373.991,
-                  "cuda_time_us": 779.9669999999999,
-                  "pct_cuda_time": 0.8192932823774374,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 31.831,
-                      "cuda_time_us": 270.143,
-                      "pct_cuda_time": 0.283763729979971,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 269.407,
-                          "pct_cuda_time": 0.2829906205332511,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 113.59,
-                      "cuda_time_us": 53.664,
-                      "pct_cuda_time": 0.056369762702143555,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 53.664,
-                          "pct_cuda_time": 0.056369762702143555,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 154.238,
-                      "cuda_time_us": 265.823,
-                      "pct_cuda_time": 0.2792259136622672,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.008,
-                          "pct_cuda_time": 0.024168073573548728,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 241.471,
-                          "pct_cuda_time": 0.25364607501209946,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.344,
-                          "pct_cuda_time": 0.00141176507661898,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 43.029,
-                      "cuda_time_us": 190.337,
-                      "pct_cuda_time": 0.19993387603305562,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.057,
-                          "pct_cuda_time": 0.0011102944092159686,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 189.28,
-                          "pct_cuda_time": 0.19882358162383967,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.166,
-                  "cuda_time_us": 43.456,
-                  "pct_cuda_time": 0.045647070810680354,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.456,
-                      "pct_cuda_time": 0.045647070810680354,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 98.791,
-                  "cuda_time_us": 2022.779,
-                  "pct_cuda_time": 2.1247684151177557,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.875,
-                      "cuda_time_us": 1266.333,
-                      "pct_cuda_time": 1.3301820720015944,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.664,
-                          "pct_cuda_time": 0.001747899618671118,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1264.669,
-                          "pct_cuda_time": 1.3284341723829232,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.15,
-                      "cuda_time_us": 174.752,
-                      "pct_cuda_time": 0.1835630734146726,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.752,
-                          "pct_cuda_time": 0.1835630734146726,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 31.702,
-                      "cuda_time_us": 581.694,
-                      "pct_cuda_time": 0.6110232697014887,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.088,
-                          "pct_cuda_time": 0.0011428574429772696,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 580.606,
-                          "pct_cuda_time": 0.6098804122585115,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 526.001,
-              "cuda_time_us": 2887.9970000000003,
-              "pct_cuda_time": 3.033611090759215,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.739,
-                  "cuda_time_us": 43.744,
-                  "pct_cuda_time": 0.04594959189852727,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.744,
-                      "pct_cuda_time": 0.04594959189852727,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 381.098,
-                  "cuda_time_us": 779.7440000000001,
-                  "pct_cuda_time": 0.819059038618445,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 31.51,
-                      "cuda_time_us": 271.264,
-                      "pct_cuda_time": 0.28494125129759745,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.312,
-                          "pct_cuda_time": 0.0013781516224137661,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 269.952,
-                          "pct_cuda_time": 0.28356309967518367,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 110.113,
-                      "cuda_time_us": 53.919,
-                      "pct_cuda_time": 0.05663761991534135,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 53.919,
-                          "pct_cuda_time": 0.05663761991534135,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 166.246,
-                      "cuda_time_us": 265.40900000000005,
-                      "pct_cuda_time": 0.2787910395984873,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.008,
-                          "pct_cuda_time": 0.024168073573548728,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 241.056,
-                          "pct_cuda_time": 0.2532101505278756,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.345,
-                          "pct_cuda_time": 0.0014128154970628928,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 41.999,
-                      "cuda_time_us": 189.152,
-                      "pct_cuda_time": 0.1986891278070188,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.416,
-                          "pct_cuda_time": 0.1979160183602989,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.82,
-                  "cuda_time_us": 43.584,
-                  "pct_cuda_time": 0.04578152462750121,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.584,
-                      "pct_cuda_time": 0.04578152462750121,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 98.561,
-                  "cuda_time_us": 2020.925,
-                  "pct_cuda_time": 2.122820935614741,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.333,
-                      "cuda_time_us": 1263.006,
-                      "pct_cuda_time": 1.326687323184696,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.057,
-                          "pct_cuda_time": 0.0011102944092159686,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1261.949,
-                          "pct_cuda_time": 1.32557702877548,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.256,
-                      "cuda_time_us": 175.072,
-                      "pct_cuda_time": 0.18389920795672474,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 175.072,
-                          "pct_cuda_time": 0.18389920795672474,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 31.836,
-                      "cuda_time_us": 582.847,
-                      "pct_cuda_time": 0.6122344044733203,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.376,
-                          "pct_cuda_time": 0.0014453785308241936,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 581.471,
-                          "pct_cuda_time": 0.6107890259424962,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 522.652,
-              "cuda_time_us": 2888.0899999999997,
-              "pct_cuda_time": 3.033708779860498,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.747,
-                  "cuda_time_us": 44.288,
-                  "pct_cuda_time": 0.04652102062001591,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.288,
-                      "pct_cuda_time": 0.04652102062001591,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 371.043,
-                  "cuda_time_us": 779.198,
-                  "pct_cuda_time": 0.8184855090560683,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 31.005,
-                      "cuda_time_us": 271.135,
-                      "pct_cuda_time": 0.2848057470603326,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 270.399,
-                          "pct_cuda_time": 0.28403263761361275,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 107.188,
-                      "cuda_time_us": 54.112,
-                      "pct_cuda_time": 0.05684035106101654,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.112,
-                          "pct_cuda_time": 0.05684035106101654,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 156.677,
-                      "cuda_time_us": 264.127,
-                      "pct_cuda_time": 0.27744440058939085,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.24,
-                          "pct_cuda_time": 0.023361350672623595,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.383,
-                          "pct_cuda_time": 0.2525032175691222,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.001579832347645049,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 45.195,
-                      "cuda_time_us": 189.82399999999998,
-                      "pct_cuda_time": 0.19939501034532828,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.408,
-                          "pct_cuda_time": 0.0014789919850294075,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.416,
-                          "pct_cuda_time": 0.1979160183602989,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 18.662,
-                  "cuda_time_us": 44.096,
-                  "pct_cuda_time": 0.04631933989478462,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.096,
-                      "pct_cuda_time": 0.04631933989478462,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 102.544,
-                  "cuda_time_us": 2020.5079999999998,
-                  "pct_cuda_time": 2.122382910289629,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 36.685,
-                      "cuda_time_us": 1261.981,
-                      "pct_cuda_time": 1.3256106422296852,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.768,
-                          "pct_cuda_time": 0.0008067229009251313,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1261.213,
-                          "pct_cuda_time": 1.3248039193287602,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.57,
-                      "cuda_time_us": 174.432,
-                      "pct_cuda_time": 0.18322693887262045,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.432,
-                          "pct_cuda_time": 0.18322693887262045,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 32.653,
-                      "cuda_time_us": 584.0949999999999,
-                      "pct_cuda_time": 0.6135453291873236,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.536,
-                          "pct_cuda_time": 0.0016134458018502626,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 582.559,
-                          "pct_cuda_time": 0.6119318833854734,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 524.462,
-              "cuda_time_us": 2886.202,
-              "pct_cuda_time": 3.031725586062391,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.254,
-                  "cuda_time_us": 43.712,
-                  "pct_cuda_time": 0.04591597844432207,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.712,
-                      "pct_cuda_time": 0.04591597844432207,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 369.849,
-                  "cuda_time_us": 778.687,
-                  "pct_cuda_time": 0.8179487442092289,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 32.606,
-                      "cuda_time_us": 270.079,
-                      "pct_cuda_time": 0.28369650307156064,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 269.343,
-                          "pct_cuda_time": 0.28292339362484076,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 99.906,
-                      "cuda_time_us": 54.432,
-                      "pct_cuda_time": 0.057176485603068684,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.432,
-                          "pct_cuda_time": 0.057176485603068684,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 157.013,
-                      "cuda_time_us": 264.512,
-                      "pct_cuda_time": 0.27784881246029736,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.4,
-                          "pct_cuda_time": 0.023529417943649662,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.384,
-                          "pct_cuda_time": 0.2525042679895661,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.728,
-                          "pct_cuda_time": 0.0018151265270815455,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 44.025,
-                      "cuda_time_us": 189.664,
-                      "pct_cuda_time": 0.1992269430743022,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.928,
-                          "pct_cuda_time": 0.19845383362758232,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.634,
-                  "cuda_time_us": 44.352,
-                  "pct_cuda_time": 0.04658824752842633,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.352,
-                      "pct_cuda_time": 0.04658824752842633,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 106.93,
-                  "cuda_time_us": 2019.451,
-                  "pct_cuda_time": 2.1212726158804136,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 35.64,
-                      "cuda_time_us": 1263.325,
-                      "pct_cuda_time": 1.3270224073063042,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.088,
-                          "pct_cuda_time": 0.0011428574429772696,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1262.237,
-                          "pct_cuda_time": 1.3258795498633271,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.815,
-                      "cuda_time_us": 174.528,
-                      "pct_cuda_time": 0.1833277792352361,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.528,
-                          "pct_cuda_time": 0.1833277792352361,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 37.964,
-                      "cuda_time_us": 581.598,
-                      "pct_cuda_time": 0.6109224293388731,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 580.862,
-                          "pct_cuda_time": 0.6101493198921532,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 519.703,
-              "cuda_time_us": 2888.6989999999996,
-              "pct_cuda_time": 3.034348485910841,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.059,
-                  "cuda_time_us": 44.193,
-                  "pct_cuda_time": 0.04642123067784418,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.193,
-                      "pct_cuda_time": 0.04642123067784418,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 367.633,
-                  "cuda_time_us": 780.255,
-                  "pct_cuda_time": 0.8195958034652843,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 32.514,
-                      "cuda_time_us": 270.432,
-                      "pct_cuda_time": 0.2840673014882619,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.024,
-                          "pct_cuda_time": 0.001075630534566842,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 269.408,
-                          "pct_cuda_time": 0.28299167095369504,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 102.285,
-                      "cuda_time_us": 54.368,
-                      "pct_cuda_time": 0.057109258694658264,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.368,
-                          "pct_cuda_time": 0.057109258694658264,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 157.515,
-                      "cuda_time_us": 264.575,
-                      "pct_cuda_time": 0.27791498894826383,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.528,
-                          "pct_cuda_time": 0.02366387176047052,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.576,
-                          "pct_cuda_time": 0.2527059487147974,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.471,
-                          "pct_cuda_time": 0.0015451684729959224,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 44.42,
-                      "cuda_time_us": 190.88,
-                      "pct_cuda_time": 0.20050425433410035,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.024,
-                          "pct_cuda_time": 0.001075630534566842,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 189.856,
-                          "pct_cuda_time": 0.19942862379953352,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 18.138,
-                  "cuda_time_us": 43.84,
-                  "pct_cuda_time": 0.04605043226114292,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.84,
-                      "pct_cuda_time": 0.04605043226114292,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 102.238,
-                  "cuda_time_us": 2020.4109999999996,
-                  "pct_cuda_time": 2.1222810195065693,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 35.5,
-                      "cuda_time_us": 1263.3249999999998,
-                      "pct_cuda_time": 1.327022407306304,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.503,
-                          "pct_cuda_time": 0.001578781927201136,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1261.822,
-                          "pct_cuda_time": 1.3254436253791029,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 22.382,
-                      "cuda_time_us": 174.591,
-                      "pct_cuda_time": 0.18339395572320263,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.591,
-                          "pct_cuda_time": 0.18339395572320263,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 32.58,
-                      "cuda_time_us": 582.495,
-                      "pct_cuda_time": 0.611864656477063,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.056,
-                          "pct_cuda_time": 0.0011092439887720558,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 581.439,
-                          "pct_cuda_time": 0.6107554124882909,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 518.174,
-              "cuda_time_us": 2889.498,
-              "pct_cuda_time": 3.0351877718455276,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.858,
-                  "cuda_time_us": 44.352,
-                  "pct_cuda_time": 0.04658824752842633,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.352,
-                      "pct_cuda_time": 0.04658824752842633,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 373.315,
-                  "cuda_time_us": 778.111,
-                  "pct_cuda_time": 0.817343702033535,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 31.84,
-                      "cuda_time_us": 269.087,
-                      "pct_cuda_time": 0.282654485991199,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 268.351,
-                          "pct_cuda_time": 0.2818813765444791,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 115.585,
-                      "cuda_time_us": 54.208,
-                      "pct_cuda_time": 0.05694119142363219,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.208,
-                          "pct_cuda_time": 0.05694119142363219,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 154.912,
-                      "cuda_time_us": 264.32,
-                      "pct_cuda_time": 0.27764713173506606,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.464,
-                          "pct_cuda_time": 0.023596644852060093,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.512,
-                          "pct_cuda_time": 0.25263872180638697,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.344,
-                          "pct_cuda_time": 0.00141176507661898,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 41.914,
-                      "cuda_time_us": 190.49599999999998,
-                      "pct_cuda_time": 0.2001008928836378,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 189.76,
-                          "pct_cuda_time": 0.19932778343691787,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.345,
-                  "cuda_time_us": 44.128,
-                  "pct_cuda_time": 0.04635295334898984,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.128,
-                      "pct_cuda_time": 0.04635295334898984,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 97.913,
-                  "cuda_time_us": 2022.907,
-                  "pct_cuda_time": 2.1249028689345764,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.063,
-                      "cuda_time_us": 1266.2369999999999,
-                      "pct_cuda_time": 1.3300812316389785,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.024,
-                          "pct_cuda_time": 0.001075630534566842,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1265.213,
-                          "pct_cuda_time": 1.3290056011044116,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.678,
-                      "cuda_time_us": 174.719,
-                      "pct_cuda_time": 0.18352840954002347,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.719,
-                          "pct_cuda_time": 0.18352840954002347,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 31.026,
-                      "cuda_time_us": 581.951,
-                      "pct_cuda_time": 0.6112932277555744,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 581.215,
-                          "pct_cuda_time": 0.6105201183088546,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 514.779,
-              "cuda_time_us": 2886.105,
-              "pct_cuda_time": 3.0316236952793307,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.004,
-                  "cuda_time_us": 43.904,
-                  "pct_cuda_time": 0.04611765916955335,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.904,
-                      "pct_cuda_time": 0.04611765916955335,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 366.733,
-                  "cuda_time_us": 779.39,
-                  "pct_cuda_time": 0.8186871897812996,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 30.587,
-                      "cuda_time_us": 270.368,
-                      "pct_cuda_time": 0.28400007457985144,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.024,
-                          "pct_cuda_time": 0.001075630534566842,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 269.344,
-                          "pct_cuda_time": 0.2829244440452846,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 100.786,
-                      "cuda_time_us": 54.4,
-                      "pct_cuda_time": 0.05714287214886347,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.4,
-                          "pct_cuda_time": 0.05714287214886347,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 152.201,
-                      "cuda_time_us": 264.959,
-                      "pct_cuda_time": 0.27831835039872643,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.4,
-                          "pct_cuda_time": 0.023529417943649662,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.863,
-                          "pct_cuda_time": 0.25300741938220045,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.696,
-                          "pct_cuda_time": 0.0017815130728763317,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 43.511,
-                      "cuda_time_us": 189.66299999999998,
-                      "pct_cuda_time": 0.19922589265385832,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.927,
-                          "pct_cuda_time": 0.19845278320713838,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.895,
-                  "cuda_time_us": 43.648,
-                  "pct_cuda_time": 0.045848751535911635,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.648,
-                      "pct_cuda_time": 0.045848751535911635,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 101.709,
-                  "cuda_time_us": 2019.163,
-                  "pct_cuda_time": 2.1209700947925665,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 35.532,
-                      "cuda_time_us": 1262.461,
-                      "pct_cuda_time": 1.3261148440427635,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.768,
-                          "pct_cuda_time": 0.0008067229009251313,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1261.693,
-                          "pct_cuda_time": 1.3253081211418383,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.834,
-                      "cuda_time_us": 174.368,
-                      "pct_cuda_time": 0.18315971196421005,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.368,
-                          "pct_cuda_time": 0.18315971196421005,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 32.864,
-                      "cuda_time_us": 582.3340000000001,
-                      "pct_cuda_time": 0.6116955387855931,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.312,
-                          "pct_cuda_time": 0.0013781516224137661,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 581.022,
-                          "pct_cuda_time": 0.6103173871631794,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 534.281,
-              "cuda_time_us": 2889.374,
-              "pct_cuda_time": 3.0350575197104823,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.113,
-                  "cuda_time_us": 44.641,
-                  "pct_cuda_time": 0.04689181903671717,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.641,
-                      "pct_cuda_time": 0.04689181903671717,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 389.037,
-                  "cuda_time_us": 779.5830000000001,
-                  "pct_cuda_time": 0.818889920926975,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 31.563,
-                      "cuda_time_us": 270.94500000000005,
-                      "pct_cuda_time": 0.28460616717598924,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.737,
-                          "pct_cuda_time": 0.0007741598671638304,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 270.208,
-                          "pct_cuda_time": 0.2838320073088254,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 109.628,
-                      "cuda_time_us": 54.048,
-                      "pct_cuda_time": 0.05677312415260612,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.048,
-                          "pct_cuda_time": 0.05677312415260612,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 166.293,
-                      "cuda_time_us": 265.43800000000005,
-                      "pct_cuda_time": 0.2788215017913607,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.623,
-                          "pct_cuda_time": 0.02376366170264225,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 241.311,
-                          "pct_cuda_time": 0.2534780077410734,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.001579832347645049,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 43.82,
-                      "cuda_time_us": 189.152,
-                      "pct_cuda_time": 0.1986891278070188,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.416,
-                          "pct_cuda_time": 0.1979160183602989,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.42,
-                  "cuda_time_us": 43.2,
-                  "pct_cuda_time": 0.04537816317703865,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.2,
-                      "pct_cuda_time": 0.04537816317703865,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 97.672,
-                  "cuda_time_us": 2021.9499999999998,
-                  "pct_cuda_time": 2.1238976165697516,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.003,
-                      "cuda_time_us": 1264.127,
-                      "pct_cuda_time": 1.3278648445023222,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.057,
-                          "pct_cuda_time": 0.0011102944092159686,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1263.07,
-                          "pct_cuda_time": 1.3267545500931062,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.313,
-                      "cuda_time_us": 174.24,
-                      "pct_cuda_time": 0.18302525814738918,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.24,
-                          "pct_cuda_time": 0.18302525814738918,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 31.258,
-                      "cuda_time_us": 583.583,
-                      "pct_cuda_time": 0.6130075139200403,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 582.847,
-                          "pct_cuda_time": 0.6122344044733203,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 489.202,
-              "cuda_time_us": 2886.265,
-              "pct_cuda_time": 3.0317917625503568,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 13.907,
-                  "cuda_time_us": 45.376,
-                  "pct_cuda_time": 0.04766387806299318,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 45.376,
-                      "pct_cuda_time": 0.04766387806299318,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 348.722,
-                  "cuda_time_us": 778.2379999999999,
-                  "pct_cuda_time": 0.817477105429912,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 30.863,
-                      "cuda_time_us": 270.175,
-                      "pct_cuda_time": 0.2837973434341763,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.024,
-                          "pct_cuda_time": 0.001075630534566842,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 269.151,
-                          "pct_cuda_time": 0.2827217128996094,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 104.311,
-                      "cuda_time_us": 54.015,
-                      "pct_cuda_time": 0.056738460277956995,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.015,
-                          "pct_cuda_time": 0.056738460277956995,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 144.675,
-                      "cuda_time_us": 264.928,
-                      "pct_cuda_time": 0.2782857873649651,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.336,
-                          "pct_cuda_time": 0.023462191035239235,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 241.28,
-                          "pct_cuda_time": 0.2534454447073121,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.312,
-                          "pct_cuda_time": 0.0013781516224137661,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 39.548,
-                      "cuda_time_us": 189.11999999999998,
-                      "pct_cuda_time": 0.19865551435281356,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.057,
-                          "pct_cuda_time": 0.0011102944092159686,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.063,
-                          "pct_cuda_time": 0.19754521994359764,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.886,
-                  "cuda_time_us": 43.04,
-                  "pct_cuda_time": 0.04521009590601257,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.04,
-                      "pct_cuda_time": 0.04521009590601257,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 96.733,
-                  "cuda_time_us": 2019.611,
-                  "pct_cuda_time": 2.1214406831514396,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 33.556,
-                      "cuda_time_us": 1262.621,
-                      "pct_cuda_time": 1.3262829113137895,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1261.885,
-                          "pct_cuda_time": 1.3255098018670695,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.202,
-                      "cuda_time_us": 173.855,
-                      "pct_cuda_time": 0.18262084627648267,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 173.855,
-                          "pct_cuda_time": 0.18262084627648267,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 31.191,
-                      "cuda_time_us": 583.135,
-                      "pct_cuda_time": 0.6125369255611672,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.056,
-                          "pct_cuda_time": 0.0011092439887720558,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 582.079,
-                          "pct_cuda_time": 0.6114276815723952,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 518.435,
-              "cuda_time_us": 2887.2599999999998,
-              "pct_cuda_time": 3.03283693089205,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.369,
-                  "cuda_time_us": 44.8,
-                  "pct_cuda_time": 0.047058835887299325,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.8,
-                      "pct_cuda_time": 0.047058835887299325,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 371.191,
-                  "cuda_time_us": 777.8549999999999,
-                  "pct_cuda_time": 0.8170747943998932,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 32.771,
-                      "cuda_time_us": 269.792,
-                      "pct_cuda_time": 0.2833950324041576,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.344,
-                          "pct_cuda_time": 0.00141176507661898,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 268.448,
-                          "pct_cuda_time": 0.2819832673275386,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 101.088,
-                      "cuda_time_us": 54.272,
-                      "pct_cuda_time": 0.057008418332042614,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.272,
-                          "pct_cuda_time": 0.057008418332042614,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 152.609,
-                      "cuda_time_us": 264.159,
-                      "pct_cuda_time": 0.27747801404359607,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.272,
-                          "pct_cuda_time": 0.02339496412682881,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.511,
-                          "pct_cuda_time": 0.25263767138594306,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.376,
-                          "pct_cuda_time": 0.0014453785308241936,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 44.91,
-                      "cuda_time_us": 189.63199999999998,
-                      "pct_cuda_time": 0.199193329620097,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.896,
-                          "pct_cuda_time": 0.19842022017337707,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.96,
-                  "cuda_time_us": 43.392,
-                  "pct_cuda_time": 0.04557984390226993,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.392,
-                      "pct_cuda_time": 0.04557984390226993,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 100.011,
-                  "cuda_time_us": 2021.213,
-                  "pct_cuda_time": 2.123123456702588,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 35.396,
-                      "cuda_time_us": 1263.4859999999999,
-                      "pct_cuda_time": 1.327191524997774,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.12,
-                          "pct_cuda_time": 0.0011764708971824835,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1262.366,
-                          "pct_cuda_time": 1.3260150541005917,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.404,
-                      "cuda_time_us": 174.688,
-                      "pct_cuda_time": 0.18349584650626216,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.688,
-                          "pct_cuda_time": 0.18349584650626216,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 31.775,
-                      "cuda_time_us": 583.039,
-                      "pct_cuda_time": 0.6124360851985516,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 582.303,
-                          "pct_cuda_time": 0.6116629757518317,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 503.524,
-              "cuda_time_us": 2890.0730000000003,
-              "pct_cuda_time": 3.035791763600778,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.693,
-                  "cuda_time_us": 44.544,
-                  "pct_cuda_time": 0.04678992825365762,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.544,
-                      "pct_cuda_time": 0.04678992825365762,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 354.327,
-                  "cuda_time_us": 779.232,
-                  "pct_cuda_time": 0.8185212233511614,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 31.0,
-                      "cuda_time_us": 269.889,
-                      "pct_cuda_time": 0.2834969231872172,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.993,
-                          "pct_cuda_time": 0.001043067500805541,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 268.896,
-                          "pct_cuda_time": 0.2824538556864117,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 104.924,
-                      "cuda_time_us": 53.888,
-                      "pct_cuda_time": 0.056605056881580046,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 53.888,
-                          "pct_cuda_time": 0.056605056881580046,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 147.664,
-                      "cuda_time_us": 264.511,
-                      "pct_cuda_time": 0.27784776203985345,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.304,
-                          "pct_cuda_time": 0.023428577581034022,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.703,
-                          "pct_cuda_time": 0.25283935211117436,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.001579832347645049,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 40.534,
-                      "cuda_time_us": 190.944,
-                      "pct_cuda_time": 0.20057148124251076,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.44,
-                          "pct_cuda_time": 0.0015126054392346213,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 189.504,
-                          "pct_cuda_time": 0.19905887580327616,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.955,
-                  "cuda_time_us": 43.328,
-                  "pct_cuda_time": 0.045512616993859493,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.328,
-                      "pct_cuda_time": 0.045512616993859493,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 103.164,
-                  "cuda_time_us": 2022.9690000000003,
-                  "pct_cuda_time": 2.124967995002099,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 33.35,
-                      "cuda_time_us": 1265.4050000000002,
-                      "pct_cuda_time": 1.3292072818296432,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1264.669,
-                          "pct_cuda_time": 1.3284341723829232,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.654,
-                      "cuda_time_us": 174.911,
-                      "pct_cuda_time": 0.18373009026525475,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.911,
-                          "pct_cuda_time": 0.18373009026525475,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 38.097,
-                      "cuda_time_us": 582.653,
-                      "pct_cuda_time": 0.6120306229072013,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.311,
-                          "pct_cuda_time": 0.001377101201969853,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 581.342,
-                          "pct_cuda_time": 0.6106535217052315,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 500.18,
-              "cuda_time_us": 2885.53,
-              "pct_cuda_time": 3.0310197035240813,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.534,
-                  "cuda_time_us": 44.736,
-                  "pct_cuda_time": 0.046991608978888905,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.736,
-                      "pct_cuda_time": 0.046991608978888905,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 354.171,
-                  "cuda_time_us": 777.311,
-                  "pct_cuda_time": 0.8165033656784048,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 31.562,
-                      "cuda_time_us": 269.59999999999997,
-                      "pct_cuda_time": 0.2831933516789263,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 268.864,
-                          "pct_cuda_time": 0.28242024223220635,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 99.186,
-                      "cuda_time_us": 53.984,
-                      "pct_cuda_time": 0.0567058972441957,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 53.984,
-                          "pct_cuda_time": 0.0567058972441957,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 154.066,
-                      "cuda_time_us": 264.512,
-                      "pct_cuda_time": 0.27784881246029736,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.56,
-                          "pct_cuda_time": 0.023697485214675733,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.448,
-                          "pct_cuda_time": 0.25257149489797653,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.001579832347645049,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 40.161,
-                      "cuda_time_us": 189.215,
-                      "pct_cuda_time": 0.19875530429498534,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.056,
-                          "pct_cuda_time": 0.0011092439887720558,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.159,
-                          "pct_cuda_time": 0.19764606030621326,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.784,
-                  "cuda_time_us": 43.456,
-                  "pct_cuda_time": 0.045647070810680354,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.456,
-                      "pct_cuda_time": 0.045647070810680354,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 99.524,
-                  "cuda_time_us": 2020.027,
-                  "pct_cuda_time": 2.1218776580561074,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.921,
-                      "cuda_time_us": 1262.749,
-                      "pct_cuda_time": 1.3264173651306104,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.768,
-                          "pct_cuda_time": 0.0008067229009251313,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1261.981,
-                          "pct_cuda_time": 1.3256106422296852,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.192,
-                      "cuda_time_us": 175.008,
-                      "pct_cuda_time": 0.18383198104831433,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 175.008,
-                          "pct_cuda_time": 0.18383198104831433,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 32.547,
-                      "cuda_time_us": 582.27,
-                      "pct_cuda_time": 0.6116283118771826,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 581.534,
-                          "pct_cuda_time": 0.6108552024304627,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 546.694,
-              "cuda_time_us": 2891.098,
-              "pct_cuda_time": 3.0368684445557883,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.329,
-                  "cuda_time_us": 43.648,
-                  "pct_cuda_time": 0.045848751535911635,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.648,
-                      "pct_cuda_time": 0.045848751535911635,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 380.947,
-                  "cuda_time_us": 778.5889999999999,
-                  "pct_cuda_time": 0.8178458030057253,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 31.909,
-                      "cuda_time_us": 270.49600000000004,
-                      "pct_cuda_time": 0.28413452839667236,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.992,
-                          "pct_cuda_time": 0.001042017080361628,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 269.504,
-                          "pct_cuda_time": 0.2830925113163107,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 110.521,
-                      "cuda_time_us": 54.207,
-                      "pct_cuda_time": 0.056940141003188276,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.207,
-                          "pct_cuda_time": 0.056940141003188276,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 160.826,
-                      "cuda_time_us": 264.83,
-                      "pct_cuda_time": 0.27818284616146166,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.008,
-                          "pct_cuda_time": 0.024168073573548728,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.351,
-                          "pct_cuda_time": 0.252469604114917,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.471,
-                          "pct_cuda_time": 0.0015451684729959224,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 47.0,
-                      "cuda_time_us": 189.05599999999998,
-                      "pct_cuda_time": 0.19858828744440316,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.32,
-                          "pct_cuda_time": 0.19781517799768322,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 18.677,
-                  "cuda_time_us": 43.04,
-                  "pct_cuda_time": 0.04521009590601257,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.04,
-                      "pct_cuda_time": 0.04521009590601257,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 117.127,
-                  "cuda_time_us": 2025.821,
-                  "pct_cuda_time": 2.1279637941081386,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 37.59,
-                      "cuda_time_us": 1266.046,
-                      "pct_cuda_time": 1.3298806013341913,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.44,
-                          "pct_cuda_time": 0.0015126054392346213,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1264.606,
-                          "pct_cuda_time": 1.3283679958949568,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 24.435,
-                      "cuda_time_us": 174.624,
-                      "pct_cuda_time": 0.18342861959785173,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.624,
-                          "pct_cuda_time": 0.18342861959785173,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 34.606,
-                      "cuda_time_us": 585.151,
-                      "pct_cuda_time": 0.6146545731760957,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.088,
-                          "pct_cuda_time": 0.0011428574429772696,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 584.063,
-                          "pct_cuda_time": 0.6135117157331185,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 498.057,
-              "cuda_time_us": 2888.92,
-              "pct_cuda_time": 3.0345806288289463,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.883,
-                  "cuda_time_us": 44.383,
-                  "pct_cuda_time": 0.04662081056218764,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.383,
-                      "pct_cuda_time": 0.04662081056218764,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 351.15,
-                  "cuda_time_us": 778.7819999999999,
-                  "pct_cuda_time": 0.8180485341514006,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 34.073,
-                      "cuda_time_us": 270.143,
-                      "pct_cuda_time": 0.283763729979971,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 269.407,
-                          "pct_cuda_time": 0.2829906205332511,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 98.165,
-                      "cuda_time_us": 53.472,
-                      "pct_cuda_time": 0.056168081976912275,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 53.472,
-                          "pct_cuda_time": 0.056168081976912275,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 149.239,
-                      "cuda_time_us": 264.96,
-                      "pct_cuda_time": 0.2783194008191703,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.976,
-                          "pct_cuda_time": 0.02413446011934351,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.64,
-                          "pct_cuda_time": 0.25277317562320784,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.344,
-                          "pct_cuda_time": 0.00141176507661898,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 40.552,
-                      "cuda_time_us": 190.207,
-                      "pct_cuda_time": 0.19979732137534695,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.215,
-                          "pct_cuda_time": 0.0012762608393542118,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.992,
-                          "pct_cuda_time": 0.19852106053599275,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.642,
-                  "cuda_time_us": 44.032,
-                  "pct_cuda_time": 0.046252112986374196,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.032,
-                      "pct_cuda_time": 0.046252112986374196,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 98.386,
-                  "cuda_time_us": 2021.723,
-                  "pct_cuda_time": 2.1236591711289834,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 35.67,
-                      "cuda_time_us": 1264.157,
-                      "pct_cuda_time": 1.3278963571156397,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.768,
-                          "pct_cuda_time": 0.0008067229009251313,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1263.389,
-                          "pct_cuda_time": 1.3270896342147145,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.224,
-                      "cuda_time_us": 174.688,
-                      "pct_cuda_time": 0.18349584650626216,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.688,
-                          "pct_cuda_time": 0.18349584650626216,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 30.067,
-                      "cuda_time_us": 582.878,
-                      "pct_cuda_time": 0.6122669675070816,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.863,
-                          "pct_cuda_time": 0.0009065128430968598,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 582.015,
-                          "pct_cuda_time": 0.6113604546639848,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 518.638,
-              "cuda_time_us": 2889.399,
-              "pct_cuda_time": 3.0350837802215804,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.126,
-                  "cuda_time_us": 43.808,
-                  "pct_cuda_time": 0.046016818806937705,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.808,
-                      "pct_cuda_time": 0.046016818806937705,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 365.823,
-                  "cuda_time_us": 779.261,
-                  "pct_cuda_time": 0.8185516855440349,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 30.136,
-                      "cuda_time_us": 270.59200000000004,
-                      "pct_cuda_time": 0.284235368759288,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.992,
-                          "pct_cuda_time": 0.001042017080361628,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 269.6,
-                          "pct_cuda_time": 0.28319335167892634,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 96.881,
-                      "cuda_time_us": 53.727,
-                      "pct_cuda_time": 0.056435939190110064,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 53.727,
-                          "pct_cuda_time": 0.056435939190110064,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 167.878,
-                      "cuda_time_us": 265.279,
-                      "pct_cuda_time": 0.27865448494077855,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.528,
-                          "pct_cuda_time": 0.02366387176047052,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 241.088,
-                          "pct_cuda_time": 0.2532437639820808,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.663,
-                          "pct_cuda_time": 0.001746849198227205,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 42.891,
-                      "cuda_time_us": 189.66299999999998,
-                      "pct_cuda_time": 0.19922589265385832,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.927,
-                          "pct_cuda_time": 0.19845278320713838,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.59,
-                  "cuda_time_us": 44.223,
-                  "pct_cuda_time": 0.04645274329116157,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.223,
-                      "pct_cuda_time": 0.04645274329116157,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 99.711,
-                  "cuda_time_us": 2022.107,
-                  "pct_cuda_time": 2.1240625325794458,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.975,
-                      "cuda_time_us": 1264.6039999999998,
-                      "pct_cuda_time": 1.3283658950540687,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.024,
-                          "pct_cuda_time": 0.001075630534566842,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1263.58,
-                          "pct_cuda_time": 1.327290264519502,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.167,
-                      "cuda_time_us": 174.88,
-                      "pct_cuda_time": 0.18369752723149346,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.88,
-                          "pct_cuda_time": 0.18369752723149346,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 32.257,
-                      "cuda_time_us": 582.623,
-                      "pct_cuda_time": 0.6119991102938839,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.312,
-                          "pct_cuda_time": 0.0013781516224137661,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 581.311,
-                          "pct_cuda_time": 0.6106209586714701,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 515.238,
-              "cuda_time_us": 2892.633,
-              "pct_cuda_time": 3.0384808399371943,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 13.985,
-                  "cuda_time_us": 43.647,
-                  "pct_cuda_time": 0.045847701115467716,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.647,
-                      "pct_cuda_time": 0.045847701115467716,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 373.698,
-                  "cuda_time_us": 781.887,
-                  "pct_cuda_time": 0.8213100896297503,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 31.169,
-                      "cuda_time_us": 270.65599999999995,
-                      "pct_cuda_time": 0.28430259566769833,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.768,
-                          "pct_cuda_time": 0.0008067229009251313,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 269.888,
-                          "pct_cuda_time": 0.28349587276677324,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 115.651,
-                      "cuda_time_us": 54.944,
-                      "pct_cuda_time": 0.05771430087035211,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.944,
-                          "pct_cuda_time": 0.05771430087035211,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 154.627,
-                      "cuda_time_us": 264.79900000000004,
-                      "pct_cuda_time": 0.2781502831277004,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.463,
-                          "pct_cuda_time": 0.02359559443161618,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.671,
-                          "pct_cuda_time": 0.25280573865696915,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.665,
-                          "pct_cuda_time": 0.001748950039115031,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 41.103,
-                      "cuda_time_us": 191.488,
-                      "pct_cuda_time": 0.20114290996399942,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.088,
-                          "pct_cuda_time": 0.0011428574429772696,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 190.4,
-                          "pct_cuda_time": 0.20000005252102218,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.515,
-                  "cuda_time_us": 44.448,
-                  "pct_cuda_time": 0.04668908789104198,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.448,
-                      "pct_cuda_time": 0.04668908789104198,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 96.183,
-                  "cuda_time_us": 2022.6509999999998,
-                  "pct_cuda_time": 2.1246339613009346,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 33.105,
-                      "cuda_time_us": 1267.3890000000001,
-                      "pct_cuda_time": 1.3312913159903663,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1266.653,
-                          "pct_cuda_time": 1.3305182065436465,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.789,
-                      "cuda_time_us": 174.303,
-                      "pct_cuda_time": 0.18309143463535568,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.303,
-                          "pct_cuda_time": 0.18309143463535568,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 30.916,
-                      "cuda_time_us": 580.959,
-                      "pct_cuda_time": 0.6102512106752127,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 580.223,
-                          "pct_cuda_time": 0.6094781012284928,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 497.529,
-              "cuda_time_us": 2890.934,
-              "pct_cuda_time": 3.036696175602987,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.175,
-                  "cuda_time_us": 43.936,
-                  "pct_cuda_time": 0.04615127262375855,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.936,
-                      "pct_cuda_time": 0.04615127262375855,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 357.207,
-                  "cuda_time_us": 780.988,
-                  "pct_cuda_time": 0.8203657616506725,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 31.953,
-                      "cuda_time_us": 272.063,
-                      "pct_cuda_time": 0.28578053723228386,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.96,
-                          "pct_cuda_time": 0.0010084036261564142,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 271.103,
-                          "pct_cuda_time": 0.28477213360612746,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 100.11,
-                      "cuda_time_us": 53.888,
-                      "pct_cuda_time": 0.056605056881580046,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 53.888,
-                          "pct_cuda_time": 0.056605056881580046,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 148.878,
-                      "cuda_time_us": 265.183,
-                      "pct_cuda_time": 0.2785536445781629,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.304,
-                          "pct_cuda_time": 0.023428577581034022,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 241.567,
-                          "pct_cuda_time": 0.25374691537471517,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.312,
-                          "pct_cuda_time": 0.0013781516224137661,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 47.415,
-                      "cuda_time_us": 189.854,
-                      "pct_cuda_time": 0.19942652295864569,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.735,
-                          "pct_cuda_time": 0.0007720590262760047,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 189.119,
-                          "pct_cuda_time": 0.19865446393236966,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.619,
-                  "cuda_time_us": 43.904,
-                  "pct_cuda_time": 0.04611765916955335,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.904,
-                      "pct_cuda_time": 0.04611765916955335,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 95.559,
-                  "cuda_time_us": 2022.106,
-                  "pct_cuda_time": 2.1240614821590023,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 33.44,
-                      "cuda_time_us": 1265.117,
-                      "pct_cuda_time": 1.328904760741796,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.056,
-                          "pct_cuda_time": 0.0011092439887720558,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1264.061,
-                          "pct_cuda_time": 1.327795516753024,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.929,
-                      "cuda_time_us": 173.952,
-                      "pct_cuda_time": 0.18272273705954226,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 173.952,
-                          "pct_cuda_time": 0.18272273705954226,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 30.743,
-                      "cuda_time_us": 583.037,
-                      "pct_cuda_time": 0.6124339843576638,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.735,
-                          "pct_cuda_time": 0.0007720590262760047,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 582.302,
-                          "pct_cuda_time": 0.6116619253313879,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 510.321,
-              "cuda_time_us": 2893.3679999999995,
-              "pct_cuda_time": 3.03925289896347,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 13.627,
-                  "cuda_time_us": 44.832,
-                  "pct_cuda_time": 0.04709244934150454,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.832,
-                      "pct_cuda_time": 0.04709244934150454,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 361.755,
-                  "cuda_time_us": 781.0539999999999,
-                  "pct_cuda_time": 0.8204350893999707,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 30.153,
-                      "cuda_time_us": 272.352,
-                      "pct_cuda_time": 0.2860841087405747,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.376,
-                          "pct_cuda_time": 0.0014453785308241936,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 270.976,
-                          "pct_cuda_time": 0.2846387302097505,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 104.032,
-                      "cuda_time_us": 54.017,
-                      "pct_cuda_time": 0.056740561118844825,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.017,
-                          "pct_cuda_time": 0.056740561118844825,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 154.219,
-                      "cuda_time_us": 264.702,
-                      "pct_cuda_time": 0.2780483923446408,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.623,
-                          "pct_cuda_time": 0.02376366170264225,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.736,
-                          "pct_cuda_time": 0.25287401598582343,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.343,
-                          "pct_cuda_time": 0.001410714656175067,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 44.415,
-                      "cuda_time_us": 189.983,
-                      "pct_cuda_time": 0.19956202719591046,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.216,
-                          "pct_cuda_time": 0.0012773112597981246,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.767,
-                          "pct_cuda_time": 0.19828471593611235,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.722,
-                  "cuda_time_us": 43.808,
-                  "pct_cuda_time": 0.046016818806937705,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.808,
-                      "pct_cuda_time": 0.046016818806937705,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 101.802,
-                  "cuda_time_us": 2023.6739999999998,
-                  "pct_cuda_time": 2.125708541415057,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 36.684,
-                      "cuda_time_us": 1264.6999999999998,
-                      "pct_cuda_time": 1.3284667354166841,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.735,
-                          "pct_cuda_time": 0.0007720590262760047,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1263.965,
-                          "pct_cuda_time": 1.3276946763904083,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.156,
-                      "cuda_time_us": 174.271,
-                      "pct_cuda_time": 0.18305782118115047,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.271,
-                          "pct_cuda_time": 0.18305782118115047,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 32.317,
-                      "cuda_time_us": 584.703,
-                      "pct_cuda_time": 0.6141839848172227,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.088,
-                          "pct_cuda_time": 0.0011428574429772696,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 583.615,
-                          "pct_cuda_time": 0.6130411273742455,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 506.453,
-              "cuda_time_us": 2886.967,
-              "pct_cuda_time": 3.032529157701984,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.579,
-                  "cuda_time_us": 44.672,
-                  "pct_cuda_time": 0.04692438207047847,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.672,
-                      "pct_cuda_time": 0.04692438207047847,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 361.843,
-                  "cuda_time_us": 777.758,
-                  "pct_cuda_time": 0.8169729036168338,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 31.09,
-                      "cuda_time_us": 269.471,
-                      "pct_cuda_time": 0.28305784744166157,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 268.735,
-                          "pct_cuda_time": 0.28228473799494164,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 99.716,
-                      "cuda_time_us": 53.92,
-                      "pct_cuda_time": 0.05663867033578526,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 53.92,
-                          "pct_cuda_time": 0.05663867033578526,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 160.414,
-                      "cuda_time_us": 264.767,
-                      "pct_cuda_time": 0.27811666967349513,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.592,
-                          "pct_cuda_time": 0.023731098668880946,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.671,
-                          "pct_cuda_time": 0.25280573865696915,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.001579832347645049,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 42.245,
-                      "cuda_time_us": 189.6,
-                      "pct_cuda_time": 0.1991597161658918,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.376,
-                          "pct_cuda_time": 0.0014453785308241936,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.224,
-                          "pct_cuda_time": 0.1977143376350676,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.154,
-                  "cuda_time_us": 43.103,
-                  "pct_cuda_time": 0.045276272393979085,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.103,
-                      "pct_cuda_time": 0.045276272393979085,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 97.526,
-                  "cuda_time_us": 2021.4340000000002,
-                  "pct_cuda_time": 2.123355599620693,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 33.458,
-                      "cuda_time_us": 1264.604,
-                      "pct_cuda_time": 1.3283658950540689,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.055,
-                          "pct_cuda_time": 0.0011081935683281427,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1263.549,
-                          "pct_cuda_time": 1.3272577014857405,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.975,
-                      "cuda_time_us": 174.079,
-                      "pct_cuda_time": 0.18285614045591922,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.079,
-                          "pct_cuda_time": 0.18285614045591922,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 31.949,
-                      "cuda_time_us": 582.7510000000001,
-                      "pct_cuda_time": 0.6121335641107049,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.344,
-                          "pct_cuda_time": 0.00141176507661898,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 581.407,
-                          "pct_cuda_time": 0.6107217990340857,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 481.086,
-              "cuda_time_us": 2891.4800000000005,
-              "pct_cuda_time": 3.0372697051653637,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.318,
-                  "cuda_time_us": 44.544,
-                  "pct_cuda_time": 0.04678992825365762,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.544,
-                      "pct_cuda_time": 0.04678992825365762,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 339.956,
-                  "cuda_time_us": 779.389,
-                  "pct_cuda_time": 0.8186861393608558,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 30.614,
-                      "cuda_time_us": 270.207,
-                      "pct_cuda_time": 0.2838309568883815,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 269.471,
-                          "pct_cuda_time": 0.28305784744166157,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 95.132,
-                      "cuda_time_us": 54.24,
-                      "pct_cuda_time": 0.056974804877837404,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.24,
-                          "pct_cuda_time": 0.056974804877837404,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 147.014,
-                      "cuda_time_us": 265.40700000000004,
-                      "pct_cuda_time": 0.2787889387575994,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.656,
-                          "pct_cuda_time": 0.023798325577291373,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 241.055,
-                          "pct_cuda_time": 0.2532091001074317,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.696,
-                          "pct_cuda_time": 0.0017815130728763317,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 39.151,
-                      "cuda_time_us": 189.535,
-                      "pct_cuda_time": 0.19909143883703748,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.088,
-                          "pct_cuda_time": 0.0011428574429772696,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 188.447,
-                          "pct_cuda_time": 0.19794858139406019,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.522,
-                  "cuda_time_us": 43.488,
-                  "pct_cuda_time": 0.045680684264885564,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.488,
-                      "pct_cuda_time": 0.045680684264885564,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 97.426,
-                  "cuda_time_us": 2024.0590000000002,
-                  "pct_cuda_time": 2.1261129532859644,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.173,
-                      "cuda_time_us": 1265.853,
-                      "pct_cuda_time": 1.3296778701885161,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1265.117,
-                          "pct_cuda_time": 1.328904760741796,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.207,
-                      "cuda_time_us": 175.104,
-                      "pct_cuda_time": 0.18393282141092995,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 175.104,
-                          "pct_cuda_time": 0.18393282141092995,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 31.376,
-                      "cuda_time_us": 583.102,
-                      "pct_cuda_time": 0.6125022616865181,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.12,
-                          "pct_cuda_time": 0.0011764708971824835,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 581.982,
-                          "pct_cuda_time": 0.6113257907893357,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 530.572,
-              "cuda_time_us": 2893.7209999999995,
-              "pct_cuda_time": 3.0396236973801716,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.32,
-                  "cuda_time_us": 43.583,
-                  "pct_cuda_time": 0.04578047420705729,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.583,
-                      "pct_cuda_time": 0.04578047420705729,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 380.175,
-                  "cuda_time_us": 780.6379999999999,
-                  "pct_cuda_time": 0.8199981144953029,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 33.39,
-                      "cuda_time_us": 271.551,
-                      "pct_cuda_time": 0.28524272196500045,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.735,
-                          "pct_cuda_time": 0.0007720590262760047,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 270.816,
-                          "pct_cuda_time": 0.2844706629387244,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 106.855,
-                      "cuda_time_us": 54.048,
-                      "pct_cuda_time": 0.05677312415260612,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.048,
-                          "pct_cuda_time": 0.05677312415260612,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 166.59,
-                      "cuda_time_us": 264.799,
-                      "pct_cuda_time": 0.27815028312770035,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.464,
-                          "pct_cuda_time": 0.023596644852060093,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.863,
-                          "pct_cuda_time": 0.25300741938220045,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.472,
-                          "pct_cuda_time": 0.0015462188934398352,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 43.711,
-                      "cuda_time_us": 190.23999999999998,
-                      "pct_cuda_time": 0.19983198524999604,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 189.504,
-                          "pct_cuda_time": 0.19905887580327616,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 18.503,
-                  "cuda_time_us": 43.552,
-                  "pct_cuda_time": 0.04574791117329599,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.552,
-                      "pct_cuda_time": 0.04574791117329599,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 101.997,
-                  "cuda_time_us": 2025.9479999999999,
-                  "pct_cuda_time": 2.1280971975045153,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 36.484,
-                      "cuda_time_us": 1268.062,
-                      "pct_cuda_time": 1.3319982489491198,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.408,
-                          "pct_cuda_time": 0.0014789919850294075,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1266.654,
-                          "pct_cuda_time": 1.3305192569640902,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 22.161,
-                      "cuda_time_us": 174.783,
-                      "pct_cuda_time": 0.18359563644843388,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.783,
-                          "pct_cuda_time": 0.18359563644843388,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 32.055,
-                      "cuda_time_us": 583.103,
-                      "pct_cuda_time": 0.6125033121069621,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 582.367,
-                          "pct_cuda_time": 0.6117302026602421,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 504.368,
-              "cuda_time_us": 2888.059,
-              "pct_cuda_time": 3.0336762168267373,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.053,
-                  "cuda_time_us": 43.584,
-                  "pct_cuda_time": 0.04578152462750121,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.584,
-                      "pct_cuda_time": 0.04578152462750121,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 360.172,
-                  "cuda_time_us": 778.495,
-                  "pct_cuda_time": 0.8177470634839976,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 31.913,
-                      "cuda_time_us": 269.887,
-                      "pct_cuda_time": 0.28349482234632933,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.024,
-                          "pct_cuda_time": 0.001075630534566842,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 268.863,
-                          "pct_cuda_time": 0.2824191918117625,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 98.704,
-                      "cuda_time_us": 54.144,
-                      "pct_cuda_time": 0.05687396451522177,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 54.144,
-                          "pct_cuda_time": 0.05687396451522177,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 161.742,
-                      "cuda_time_us": 264.352,
-                      "pct_cuda_time": 0.27768074518927127,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.88,
-                          "pct_cuda_time": 0.02403361975672787,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.128,
-                          "pct_cuda_time": 0.2522353603559244,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.344,
-                          "pct_cuda_time": 0.00141176507661898,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 40.174,
-                      "cuda_time_us": 190.112,
-                      "pct_cuda_time": 0.19969753143317523,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.057,
-                          "pct_cuda_time": 0.0011102944092159686,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 189.055,
-                          "pct_cuda_time": 0.19858723702395925,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.077,
-                  "cuda_time_us": 43.296,
-                  "pct_cuda_time": 0.04547900353965428,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.296,
-                      "pct_cuda_time": 0.04547900353965428,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 97.604,
-                  "cuda_time_us": 2022.684,
-                  "pct_cuda_time": 2.124668625175584,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.16,
-                      "cuda_time_us": 1264.221,
-                      "pct_cuda_time": 1.3279635840240502,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1263.485,
-                          "pct_cuda_time": 1.3271904745773302,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.809,
-                      "cuda_time_us": 174.847,
-                      "pct_cuda_time": 0.18366286335684434,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.847,
-                          "pct_cuda_time": 0.18366286335684434,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 31.664,
-                      "cuda_time_us": 583.616,
-                      "pct_cuda_time": 0.6130421777946894,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.185,
-                          "pct_cuda_time": 0.001244748226036824,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 582.431,
-                          "pct_cuda_time": 0.6117974295686527,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 487.127,
-              "cuda_time_us": 2892.026,
-              "pct_cuda_time": 3.0378432347277395,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 13.862,
-                  "cuda_time_us": 43.904,
-                  "pct_cuda_time": 0.04611765916955335,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.904,
-                      "pct_cuda_time": 0.04611765916955335,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 350.574,
-                  "cuda_time_us": 780.0300000000001,
-                  "pct_cuda_time": 0.8193594588654041,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 30.098,
-                      "cuda_time_us": 270.784,
-                      "pct_cuda_time": 0.28443704948451926,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 270.048,
-                          "pct_cuda_time": 0.2836639400377993,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 98.322,
-                      "cuda_time_us": 53.92,
-                      "pct_cuda_time": 0.05663867033578526,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 53.92,
-                          "pct_cuda_time": 0.05663867033578526,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 155.635,
-                      "cuda_time_us": 265.024,
-                      "pct_cuda_time": 0.27838662772758077,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.816,
-                          "pct_cuda_time": 0.023966392848317444,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.512,
-                          "pct_cuda_time": 0.25263872180638697,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.696,
-                          "pct_cuda_time": 0.0017815130728763317,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 39.524,
-                      "cuda_time_us": 190.30200000000002,
-                      "pct_cuda_time": 0.19989711131751872,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.735,
-                          "pct_cuda_time": 0.0007720590262760047,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 189.567,
-                          "pct_cuda_time": 0.1991250522912427,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.869,
-                  "cuda_time_us": 42.688,
-                  "pct_cuda_time": 0.04484034790975522,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 42.688,
-                      "pct_cuda_time": 0.04484034790975522,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 92.808,
-                  "cuda_time_us": 2025.404,
-                  "pct_cuda_time": 2.127525768783027,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 32.394,
-                      "cuda_time_us": 1265.981,
-                      "pct_cuda_time": 1.329812324005337,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.088,
-                          "pct_cuda_time": 0.0011428574429772696,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1264.893,
-                          "pct_cuda_time": 1.3286694665623595,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.215,
-                      "cuda_time_us": 174.848,
-                      "pct_cuda_time": 0.18366391377728827,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 174.848,
-                          "pct_cuda_time": 0.18366391377728827,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 30.212,
-                      "cuda_time_us": 584.5749999999999,
-                      "pct_cuda_time": 0.6140495310004018,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.376,
-                          "pct_cuda_time": 0.0014453785308241936,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 583.199,
-                          "pct_cuda_time": 0.6126041524695777,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 494.076,
-              "cuda_time_us": 3203.833,
-              "pct_cuda_time": 3.3653716820828987,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 13.793,
-                  "cuda_time_us": 43.808,
-                  "pct_cuda_time": 0.046016818806937705,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 43.808,
-                      "pct_cuda_time": 0.046016818806937705,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 349.317,
-                  "cuda_time_us": 781.087,
-                  "pct_cuda_time": 0.8204697532746198,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 30.899,
-                      "cuda_time_us": 271.392,
-                      "pct_cuda_time": 0.28507570511441827,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.056,
-                          "pct_cuda_time": 0.0011092439887720558,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 270.336,
-                          "pct_cuda_time": 0.2839664611256463,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 96.661,
-                      "cuda_time_us": 53.952,
-                      "pct_cuda_time": 0.05667228378999048,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 53.952,
-                          "pct_cuda_time": 0.05667228378999048,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 150.931,
-                      "cuda_time_us": 264.863,
-                      "pct_cuda_time": 0.2782175100361108,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.463,
-                          "pct_cuda_time": 0.02359559443161618,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 240.703,
-                          "pct_cuda_time": 0.25283935211117436,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.697,
-                          "pct_cuda_time": 0.0017825634933202447,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 43.047,
-                      "cuda_time_us": 190.88,
-                      "pct_cuda_time": 0.20050425433410035,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.768,
-                          "pct_cuda_time": 0.0008067229009251313,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 190.112,
-                          "pct_cuda_time": 0.19969753143317523,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.721,
-                  "cuda_time_us": 44.64,
-                  "pct_cuda_time": 0.04689076861627326,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.64,
-                      "pct_cuda_time": 0.04689076861627326,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 99.133,
-                  "cuda_time_us": 2334.2980000000002,
-                  "pct_cuda_time": 2.4519943413850687,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.832,
-                      "cuda_time_us": 1479.6760000000002,
-                      "pct_cuda_time": 1.5542819207673109,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1478.94,
-                          "pct_cuda_time": 1.5535088113205908,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.526,
-                      "cuda_time_us": 186.144,
-                      "pct_cuda_time": 0.19552946311172872,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 186.144,
-                          "pct_cuda_time": 0.19552946311172872,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 31.294,
-                      "cuda_time_us": 668.4780000000001,
-                      "pct_cuda_time": 0.7021829575060287,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.056,
-                          "pct_cuda_time": 0.0011092439887720558,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 667.422,
-                          "pct_cuda_time": 0.7010737135172566,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 501.846,
-              "cuda_time_us": 3342.331,
-              "pct_cuda_time": 3.5108528127239524,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.015,
-                  "cuda_time_us": 44.672,
-                  "pct_cuda_time": 0.04692438207047847,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.672,
-                      "pct_cuda_time": 0.04692438207047847,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 356.278,
-                  "cuda_time_us": 911.0390000000001,
-                  "pct_cuda_time": 0.9569739908019933,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 31.694,
-                      "cuda_time_us": 312.0,
-                      "pct_cuda_time": 0.3277311785008346,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 311.264,
-                          "pct_cuda_time": 0.32695806905411473,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 95.252,
-                      "cuda_time_us": 58.944,
-                      "pct_cuda_time": 0.06191598264600383,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 58.944,
-                          "pct_cuda_time": 0.06191598264600383,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 158.141,
-                      "cuda_time_us": 317.024,
-                      "pct_cuda_time": 0.33300849081105316,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 24.064,
-                          "pct_cuda_time": 0.025277317562320784,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 291.488,
-                          "pct_cuda_time": 0.3061849543552925,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.472,
-                          "pct_cuda_time": 0.0015462188934398352,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 41.667,
-                      "cuda_time_us": 223.071,
-                      "pct_cuda_time": 0.23431833884410155,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 222.335,
-                          "pct_cuda_time": 0.23354522939738162,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.255,
-                  "cuda_time_us": 44.704,
-                  "pct_cuda_time": 0.04695799552468369,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.704,
-                      "pct_cuda_time": 0.04695799552468369,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 97.368,
-                  "cuda_time_us": 2341.916,
-                  "pct_cuda_time": 2.459996444326797,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.445,
-                      "cuda_time_us": 1487.741,
-                      "pct_cuda_time": 1.5627535616474686,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.024,
-                          "pct_cuda_time": 0.001075630534566842,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1486.717,
-                          "pct_cuda_time": 1.5616779311129019,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.028,
-                      "cuda_time_us": 186.272,
-                      "pct_cuda_time": 0.1956639169285496,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 186.272,
-                          "pct_cuda_time": 0.1956639169285496,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 30.9,
-                      "cuda_time_us": 667.903,
-                      "pct_cuda_time": 0.7015789657507787,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 667.167,
-                          "pct_cuda_time": 0.7008058563040588,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 499.387,
-              "cuda_time_us": 3345.6899999999996,
-              "pct_cuda_time": 3.514381174995055,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.544,
-                  "cuda_time_us": 45.343,
-                  "pct_cuda_time": 0.04762921418834406,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 45.343,
-                      "pct_cuda_time": 0.04762921418834406,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 348.963,
-                  "cuda_time_us": 913.343,
-                  "pct_cuda_time": 0.9593941595047685,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 29.813,
-                      "cuda_time_us": 313.472,
-                      "pct_cuda_time": 0.3292773973942744,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.44,
-                          "pct_cuda_time": 0.0015126054392346213,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 312.032,
-                          "pct_cuda_time": 0.3277647919550398,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 96.212,
-                      "cuda_time_us": 58.975,
-                      "pct_cuda_time": 0.06194854567976514,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 58.975,
-                          "pct_cuda_time": 0.06194854567976514,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 150.812,
-                      "cuda_time_us": 317.217,
-                      "pct_cuda_time": 0.33321122195672837,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 24.321,
-                          "pct_cuda_time": 0.025547275616406406,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 291.424,
-                          "pct_cuda_time": 0.30611772744688215,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.472,
-                          "pct_cuda_time": 0.0015462188934398352,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 43.116,
-                      "cuda_time_us": 223.679,
-                      "pct_cuda_time": 0.2349569944740006,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.056,
-                          "pct_cuda_time": 0.0011092439887720558,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 222.623,
-                          "pct_cuda_time": 0.23384775048522852,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.749,
-                  "cuda_time_us": 45.92,
-                  "pct_cuda_time": 0.04823530678448182,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 45.92,
-                      "pct_cuda_time": 0.04823530678448182,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 102.536,
-                  "cuda_time_us": 2341.084,
-                  "pct_cuda_time": 2.459122494517461,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 35.958,
-                      "cuda_time_us": 1487.133,
-                      "pct_cuda_time": 1.5621149060175694,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.768,
-                          "pct_cuda_time": 0.0008067229009251313,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1486.365,
-                          "pct_cuda_time": 1.5613081831166444,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.749,
-                      "cuda_time_us": 186.527,
-                      "pct_cuda_time": 0.19593177414174734,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 186.527,
-                          "pct_cuda_time": 0.19593177414174734,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 33.092,
-                      "cuda_time_us": 667.424,
-                      "pct_cuda_time": 0.7010758143581444,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.025,
-                          "pct_cuda_time": 0.0010766809550107547,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 666.399,
-                          "pct_cuda_time": 0.6999991334031336,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 505.974,
-              "cuda_time_us": 3338.263,
-              "pct_cuda_time": 3.506579702358114,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.638,
-                  "cuda_time_us": 45.984,
-                  "pct_cuda_time": 0.04830253369289224,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 45.984,
-                      "pct_cuda_time": 0.04830253369289224,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 362.856,
-                  "cuda_time_us": 909.6619999999999,
-                  "pct_cuda_time": 0.955527561850725,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 31.394,
-                      "cuda_time_us": 310.687,
-                      "pct_cuda_time": 0.326351976457977,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 309.951,
-                          "pct_cuda_time": 0.32557886701125704,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[4096, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 101.38,
-                      "cuda_time_us": 58.528,
-                      "pct_cuda_time": 0.06147900774133605,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 58.528,
-                          "pct_cuda_time": 0.06147900774133605,
-                          "trace": "_C::rotary_embedding(int64[4096], bfloat16[4096, 4096], bfloat16[4096, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 157.531,
-                      "cuda_time_us": 316.671,
-                      "pct_cuda_time": 0.3326376923943519,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 24.256,
-                          "pct_cuda_time": 0.025478998287552068,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[4096], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, false, false, true, true, true, false, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cutlass::bfloat16_t, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, false, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 290.783,
-                          "pct_cuda_time": 0.30544440794233396,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.632,
-                          "pct_cuda_time": 0.001714286164465904,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], None, None, bfloat16[4096, 32, 128], int32[2], int32[2], None, None, None, 4096, 4096, None, None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[4096, 32, 128], bfloat16[4096, 8, 128], bfloat16[4096, 8, 128], bfloat16[4096, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 42.344,
-                      "cuda_time_us": 223.77599999999998,
-                      "pct_cuda_time": 0.23505888525706012,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.408,
-                          "pct_cuda_time": 0.0014789919850294075,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 222.368,
-                          "pct_cuda_time": 0.23357989327203071,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[4096, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.488,
-                  "cuda_time_us": 44.256,
-                  "pct_cuda_time": 0.04648740716581069,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 44.256,
-                      "pct_cuda_time": 0.04648740716581069,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 96.544,
-                  "cuda_time_us": 2338.361,
-                  "pct_cuda_time": 2.456262199648686,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 33.686,
-                      "cuda_time_us": 1486.971,
-                      "pct_cuda_time": 1.5619447379056557,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.087,
-                          "pct_cuda_time": 0.0011418070225333564,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1485.884,
-                          "pct_cuda_time": 1.5608029308831224,
-                          "trace": "mm(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[4096, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[4096, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.706,
-                      "cuda_time_us": 186.047,
-                      "pct_cuda_time": 0.19542757232866914,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 186.047,
-                          "pct_cuda_time": 0.19542757232866914,
-                          "trace": "_C::silu_and_mul(bfloat16[4096, 14336], bfloat16[4096, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 31.501,
-                      "cuda_time_us": 665.343,
-                      "pct_cuda_time": 0.6988898894143616,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "Memset (Device)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 0.736,
-                          "pct_cuda_time": 0.0007731094467199176,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize128x256x64_warpgroupsize2x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 664.607,
-                          "pct_cuda_time": 0.6981167799676417,
-                          "trace": "mm(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[4096, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[4096, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "RMSNorm(weight=bfloat16[4096])",
-              "cpu_time_us": 14.776,
-              "cuda_time_us": 45.407,
-              "pct_cuda_time": 0.04769644109675447,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                  "cpu_time_us": 0,
-                  "cuda_time_us": 45.407,
-                  "pct_cuda_time": 0.04769644109675447,
-                  "trace": "_C::fused_add_rms_norm(bfloat16[4096, 4096], bfloat16[4096, 4096], bfloat16[4096], 1e-05)"
-                },
-                "children": []
-              }
-            ]
-          }
-        ]
-      },
-      {
-        "entry": {
-          "name": "LogitsProcessor",
-          "cpu_time_us": 91.588,
-          "cuda_time_us": 356.608,
-          "pct_cuda_time": 0.3745883336629027,
-          "trace": ""
-        },
-        "children": [
-          {
-            "entry": {
-              "name": "void at::native::(anonymous namespace)::indexSelectSmallIndex<c10::BFloat16, long, unsigned int, 2, 2, -2>(at::cuda::detail::TensorInfo<c10::BFloat16, unsigned int>, at::cuda::detail::TensorInfo<c10::BFloat16 const, unsigned int>, at::cuda::detail::TensorInfo<long const, unsigned int>, int, int, unsigned int, long)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 3.265,
-              "pct_cuda_time": 0.0034296227493757214,
-              "trace": "index_select(bfloat16[4096, 4096], 0, int64[1])"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memset (Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 0.768,
-              "pct_cuda_time": 0.0008067229009251313,
-              "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 128256]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 128256]) <- linear(bfloat16[1, 4096], bfloat16[128256, 4096], None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-              "cpu_time_us": 0,
-              "cuda_time_us": 352.575,
-              "pct_cuda_time": 0.37035198801260183,
-              "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 128256]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 128256]) <- linear(bfloat16[1, 4096], bfloat16[128256, 4096], None)"
-            },
-            "children": []
-          }
-        ]
-      },
-      {
-        "entry": {
-          "name": "Sampler",
-          "cpu_time_us": 78884.866,
-          "cuda_time_us": 144.192,
-          "pct_cuda_time": 0.1514622246486934,
-          "trace": ""
-        },
-        "children": [
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 3.36,
-              "pct_cuda_time": 0.00352941269154745,
-              "trace": "copy_(bfloat16[1], bfloat16[1], True) <- _to_copy(bfloat16[1], 15, 0, None, None, True, None) <- to(bfloat16[1], 15, 0, None, None, True, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.176,
-              "pct_cuda_time": 0.0022857148859545392,
-              "trace": "copy_(bfloat16[1], bfloat16[1], True) <- _to_copy(bfloat16[1], 15, 0, None, None, True, None) <- to(bfloat16[1], 15, 0, None, None, True, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.176,
-              "pct_cuda_time": 0.0022857148859545392,
-              "trace": "copy_(int32[1], int32[1], True) <- _to_copy(int32[1], 3, 0, None, None, True, None) <- to(int32[1], 3, 0, None, None, True, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.208,
-              "pct_cuda_time": 0.0023193283401597526,
-              "trace": "copy_(bfloat16[1], bfloat16[1], True) <- _to_copy(bfloat16[1], 15, 0, None, None, True, None) <- to(bfloat16[1], 15, 0, None, None, True, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.208,
-              "pct_cuda_time": 0.0023193283401597526,
-              "trace": "copy_(bfloat16[1], bfloat16[1], True) <- _to_copy(bfloat16[1], 15, 0, None, None, True, None) <- to(bfloat16[1], 15, 0, None, None, True, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.176,
-              "pct_cuda_time": 0.0022857148859545392,
-              "trace": "copy_(bfloat16[1], bfloat16[1], True) <- _to_copy(bfloat16[1], 15, 0, None, None, True, None) <- to(bfloat16[1], 15, 0, None, None, True, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.24,
-              "pct_cuda_time": 0.002352941794364967,
-              "trace": "copy_(bfloat16[1], bfloat16[1], True) <- _to_copy(bfloat16[1], 15, 0, None, None, True, None) <- to(bfloat16[1], 15, 0, None, None, True, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#7}::operator()() const::{lambda(float)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1> >(int, at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#7}::operator()() const::{lambda(float)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1>)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 4.704,
-              "pct_cuda_time": 0.0049411777681664295,
-              "trace": "copy_(float32[1, 128256], bfloat16[1, 128256], False) <- _to_copy(bfloat16[1, 128256], 6, None, None, None, False, None) <- to(bfloat16[1, 128256], 6, False, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::elementwise_kernel<128, 4, at::native::gpu_kernel_impl<at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > >(at::TensorIteratorBase&, at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > const&)::{lambda(int)#1}>(int, at::native::gpu_kernel_impl<at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > >(at::TensorIteratorBase&, at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > const&)::{lambda(int)#1})",
-              "cpu_time_us": 0,
-              "cuda_time_us": 5.376,
-              "pct_cuda_time": 0.00564706030647592,
-              "trace": "div_(float32[1, 128256], bfloat16[1, 1])"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::(anonymous namespace)::cunn_SoftMaxForward<4, float, float, float, at::native::(anonymous namespace)::SoftMaxForwardEpilogue>(float*, float const*, int)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 40.64,
-              "pct_cuda_time": 0.04268908684062153,
-              "trace": "_softmax(float32[1, 128256], -1, False) <- softmax(float32[1, 128256], -1, 6)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::(anonymous namespace)::cunn_SoftMaxForward<4, float, float, float, at::native::(anonymous namespace)::LogSoftMaxForwardEpilogue>(float*, float const*, int)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 32.576,
-              "pct_cuda_time": 0.034218496380907654,
-              "trace": "_log_softmax(float32[1, 128256], -1, False) <- log_softmax(float32[1, 128256], -1, 6)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#4}::operator()() const::{lambda(long)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1> >(int, at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#4}::operator()() const::{lambda(long)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1>)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.144,
-              "pct_cuda_time": 0.0022521014317493254,
-              "trace": "copy_(int64[1], int32[1], False) <- _to_copy(int32[1], 4, None, None, None, False, None) <- to(int32[1], 4, False, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::index_elementwise_kernel<128, 4, at::native::gpu_index_kernel<at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1}>(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>, at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1} const&)::{lambda(int)#1}>(long, at::native::gpu_index_kernel<at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1}>(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>, at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1} const&)::{lambda(int)#1})",
-              "cpu_time_us": 0,
-              "cuda_time_us": 5.312,
-              "pct_cuda_time": 0.005579833398065492,
-              "trace": "index(float32[1, 128256], None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::reduce_kernel<512, 1, at::native::ReduceOp<float, at::native::ArgMaxOps<float>, unsigned int, long, 4> >(at::native::ReduceOp<float, at::native::ArgMaxOps<float>, unsigned int, long, 4>)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 33.728,
-              "pct_cuda_time": 0.03542858073229535,
-              "trace": "argmax(float32[1, 128256], -1, False)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy DtoH (Device -> Pageable)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 3.168,
-              "pct_cuda_time": 0.003327731966316167,
-              "trace": "copy_(int64[1], int64[1], False) <- _to_copy(int64[1], 4, 0, None, None, False, None) <- to(int64[1], 4, 0, None, None, False, False, None)"
-            },
-            "children": []
-          }
-        ]
-      }
-    ]
-  },
-  "decode_1": {
-    "metadata": {
-      "num_running_seqs": 1
-    },
-    "summary_stats": [
-      {
-        "entry": {
-          "name": "LlamaForCausalLM",
-          "cuda_time_us": 6791.93,
-          "pct_cuda_time": 93.5046501558771,
-          "invocations": 1
-        },
-        "children": [
-          {
-            "entry": {
-              "name": "VocabParallelEmbedding(weight=bfloat16[128256, 4096])",
-              "cuda_time_us": 3.104,
-              "pct_cuda_time": 0.0427328364815071,
-              "invocations": 1
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "void at::native::(anonymous namespace)::indexSelectSmallIndex<c10::BFloat16, long, unsigned int, 2, 2, -2>(at::cuda::detail::TensorInfo<c10::BFloat16, unsigned int>, at::cuda::detail::TensorInfo<c10::BFloat16 const, unsigned int>, at::cuda::detail::TensorInfo<long const, unsigned int>, int, int, unsigned int, long)",
-                  "cuda_time_us": 3.104,
-                  "pct_cuda_time": 0.0427328364815071,
-                  "invocations": 1
-                },
-                "children": []
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cuda_time_us": 6785.37,
-              "pct_cuda_time": 93.41433849114814,
-              "invocations": 32
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cuda_time_us": 222.2410000000001,
-                  "pct_cuda_time": 3.059596750156773,
-                  "invocations": 64
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "void vllm::rms_norm_kernel<c10::BFloat16>(c10::BFloat16*, c10::BFloat16 const*, c10::BFloat16 const*, float, int, int)",
-                      "cuda_time_us": 4.576,
-                      "pct_cuda_time": 0.06299789295727334,
-                      "invocations": 1
-                    },
-                    "children": []
-                  },
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cuda_time_us": 217.6650000000001,
-                      "pct_cuda_time": 2.9965988571995,
-                      "invocations": 63
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cuda_time_us": 2328.683,
-                  "pct_cuda_time": 32.059030237198904,
-                  "invocations": 32
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cuda_time_us": 664.3159999999997,
-                      "pct_cuda_time": 9.145653028366256,
-                      "invocations": 32
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cuda_time_us": 664.3159999999997,
-                          "pct_cuda_time": 9.145653028366256,
-                          "invocations": 32
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cuda_time_us": 119.84,
-                      "pct_cuda_time": 1.64983992395097,
-                      "invocations": 32
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cuda_time_us": 119.84,
-                          "pct_cuda_time": 1.64983992395097,
-                          "invocations": 32
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cuda_time_us": 956.726,
-                      "pct_cuda_time": 13.171267949615451,
-                      "invocations": 32
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cuda_time_us": 74.11200000000001,
-                          "pct_cuda_time": 1.0203015390842314,
-                          "invocations": 32
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cuda_time_us": 753.1120000000001,
-                          "pct_cuda_time": 10.368109519413911,
-                          "invocations": 32
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cuda_time_us": 81.40700000000001,
-                          "pct_cuda_time": 1.1207319650290106,
-                          "invocations": 32
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cuda_time_us": 48.095,
-                          "pct_cuda_time": 0.6621249260883003,
-                          "invocations": 32
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cuda_time_us": 587.8009999999999,
-                      "pct_cuda_time": 8.092269335266222,
-                      "invocations": 32
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cuda_time_us": 587.8009999999999,
-                          "pct_cuda_time": 8.092269335266222,
-                          "invocations": 32
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cuda_time_us": 4234.446,
-                  "pct_cuda_time": 58.29571150379247,
-                  "invocations": 32
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cuda_time_us": 2560.629,
-                      "pct_cuda_time": 35.2522359364707,
-                      "invocations": 32
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cuda_time_us": 2560.629,
-                          "pct_cuda_time": 35.2522359364707,
-                          "invocations": 32
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cuda_time_us": 282.43,
-                      "pct_cuda_time": 3.8882200410670267,
-                      "invocations": 32
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cuda_time_us": 282.43,
-                          "pct_cuda_time": 3.8882200410670267,
-                          "invocations": 32
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cuda_time_us": 1391.3869999999997,
-                      "pct_cuda_time": 19.155255526254738,
-                      "invocations": 32
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cuda_time_us": 1391.3869999999997,
-                          "pct_cuda_time": 19.155255526254738,
-                          "invocations": 32
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "RMSNorm(weight=bfloat16[4096])",
-              "cuda_time_us": 3.456,
-              "pct_cuda_time": 0.0475788282474512,
-              "invocations": 1
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                  "cuda_time_us": 3.456,
-                  "pct_cuda_time": 0.0475788282474512,
-                  "invocations": 1
-                },
-                "children": []
-              }
-            ]
-          }
-        ]
-      },
-      {
-        "entry": {
-          "name": "LogitsProcessor",
-          "cuda_time_us": 347.518,
-          "pct_cuda_time": 4.784287973060691,
-          "invocations": 1
-        },
-        "children": [
-          {
-            "entry": {
-              "name": "void at::native::(anonymous namespace)::indexSelectSmallIndex<c10::BFloat16, long, unsigned int, 2, 2, -2>(at::cuda::detail::TensorInfo<c10::BFloat16, unsigned int>, at::cuda::detail::TensorInfo<c10::BFloat16 const, unsigned int>, at::cuda::detail::TensorInfo<long const, unsigned int>, int, int, unsigned int, long)",
-              "cuda_time_us": 2.624,
-              "pct_cuda_time": 0.03612466589158332,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memset (Device)",
-              "cuda_time_us": 0.735,
-              "pct_cuda_time": 0.010118761215820785,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-              "cuda_time_us": 344.159,
-              "pct_cuda_time": 4.7380445459532865,
-              "invocations": 1
-            },
-            "children": []
-          }
-        ]
-      },
-      {
-        "entry": {
-          "name": "Sampler",
-          "cuda_time_us": 124.28700000000002,
-          "pct_cuda_time": 1.7110618710622016,
-          "invocations": 1
-        },
-        "children": [
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cuda_time_us": 16.031,
-              "pct_cuda_time": 0.22069913068139183,
-              "invocations": 7
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#7}::operator()() const::{lambda(float)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1> >(int, at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#7}::operator()() const::{lambda(float)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1>)",
-              "cuda_time_us": 4.192,
-              "pct_cuda_time": 0.057711356485334334,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::elementwise_kernel<128, 4, at::native::gpu_kernel_impl<at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > >(at::TensorIteratorBase&, at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > const&)::{lambda(int)#1}>(int, at::native::gpu_kernel_impl<at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > >(at::TensorIteratorBase&, at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > const&)::{lambda(int)#1})",
-              "cuda_time_us": 4.512,
-              "pct_cuda_time": 0.062116803545283504,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::(anonymous namespace)::cunn_SoftMaxForward<4, float, float, float, at::native::(anonymous namespace)::SoftMaxForwardEpilogue>(float*, float const*, int)",
-              "cuda_time_us": 34.08,
-              "pct_cuda_time": 0.46918011188458825,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::(anonymous namespace)::cunn_SoftMaxForward<4, float, float, float, at::native::(anonymous namespace)::LogSoftMaxForwardEpilogue>(float*, float const*, int)",
-              "cuda_time_us": 27.584,
-              "pct_cuda_time": 0.3797495365676198,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#4}::operator()() const::{lambda(long)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1> >(int, at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#4}::operator()() const::{lambda(long)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1>)",
-              "cuda_time_us": 1.888,
-              "pct_cuda_time": 0.025992137653700193,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::index_elementwise_kernel<128, 4, at::native::gpu_index_kernel<at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1}>(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>, at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1} const&)::{lambda(int)#1}>(long, at::native::gpu_index_kernel<at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1}>(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>, at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1} const&)::{lambda(int)#1})",
-              "cuda_time_us": 4.64,
-              "pct_cuda_time": 0.06387898236926319,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::reduce_kernel<512, 1, at::native::ReduceOp<float, at::native::ArgMaxOps<float>, unsigned int, long, 4> >(at::native::ReduceOp<float, at::native::ArgMaxOps<float>, unsigned int, long, 4>)",
-              "cuda_time_us": 28.576,
-              "pct_cuda_time": 0.3934064224534623,
-              "invocations": 1
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy DtoH (Device -> Pageable)",
-              "cuda_time_us": 2.784,
-              "pct_cuda_time": 0.03832738942155792,
-              "invocations": 1
-            },
-            "children": []
-          }
-        ]
-      }
-    ],
-    "model_stats": [
-      {
-        "entry": {
-          "name": "LlamaForCausalLM",
-          "cpu_time_us": 17089.731,
-          "cuda_time_us": 6791.93,
-          "pct_cuda_time": 93.5046501558771,
-          "trace": ""
-        },
-        "children": [
-          {
-            "entry": {
-              "name": "VocabParallelEmbedding(weight=bfloat16[128256, 4096])",
-              "cpu_time_us": 68.255,
-              "cuda_time_us": 3.104,
-              "pct_cuda_time": 0.0427328364815071,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "void at::native::(anonymous namespace)::indexSelectSmallIndex<c10::BFloat16, long, unsigned int, 2, 2, -2>(at::cuda::detail::TensorInfo<c10::BFloat16, unsigned int>, at::cuda::detail::TensorInfo<c10::BFloat16 const, unsigned int>, at::cuda::detail::TensorInfo<long const, unsigned int>, int, int, unsigned int, long)",
-                  "cpu_time_us": 0,
-                  "cuda_time_us": 3.104,
-                  "pct_cuda_time": 0.0427328364815071,
-                  "trace": "index_select(bfloat16[128256, 4096], 0, int64[1]) <- embedding(bfloat16[128256, 4096], int64[1], -1, False, False)"
-                },
-                "children": []
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 833.35,
-              "cuda_time_us": 214.909,
-              "pct_cuda_time": 2.9586569443956856,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 50.825,
-                  "cuda_time_us": 4.576,
-                  "pct_cuda_time": 0.06299789295727334,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "void vllm::rms_norm_kernel<c10::BFloat16>(c10::BFloat16*, c10::BFloat16 const*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 4.576,
-                      "pct_cuda_time": 0.06299789295727334,
-                      "trace": "_C::rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 601.687,
-                  "cuda_time_us": 74.464,
-                  "pct_cuda_time": 1.0251475308501754,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 93.019,
-                      "cuda_time_us": 22.688,
-                      "pct_cuda_time": 0.31234619655039725,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 22.688,
-                          "pct_cuda_time": 0.31234619655039725,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 182.562,
-                      "cuda_time_us": 3.776,
-                      "pct_cuda_time": 0.051984275307400386,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.776,
-                          "pct_cuda_time": 0.051984275307400386,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 223.755,
-                      "cuda_time_us": 29.599999999999998,
-                      "pct_cuda_time": 0.4075038530452996,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.048,
-                          "pct_cuda_time": 0.02819486118367479,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.584,
-                          "pct_cuda_time": 0.32468144831825496,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.464,
-                          "pct_cuda_time": 0.033921942361608726,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 46.424,
-                      "cuda_time_us": 18.4,
-                      "pct_cuda_time": 0.2533132059470782,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.4,
-                          "pct_cuda_time": 0.2533132059470782,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 24.425,
-                  "cuda_time_us": 3.296,
-                  "pct_cuda_time": 0.04537610471747661,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.296,
-                      "pct_cuda_time": 0.04537610471747661,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 128.22,
-                  "cuda_time_us": 132.573,
-                  "pct_cuda_time": 1.8251354158707607,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 46.138,
-                      "cuda_time_us": 79.871,
-                      "pct_cuda_time": 1.0995858191412542,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.871,
-                          "pct_cuda_time": 1.0995858191412542,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 29.968,
-                      "cuda_time_us": 8.831,
-                      "pct_cuda_time": 0.12157657183253519,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.831,
-                          "pct_cuda_time": 0.12157657183253519,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 34.706,
-                      "cuda_time_us": 43.871,
-                      "pct_cuda_time": 0.603973024896971,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.871,
-                          "pct_cuda_time": 0.603973024896971,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 547.732,
-              "cuda_time_us": 214.399,
-              "pct_cuda_time": 2.9516357631438916,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.372,
-                  "cuda_time_us": 3.68,
-                  "pct_cuda_time": 0.050662641189415644,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.68,
-                      "pct_cuda_time": 0.050662641189415644,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 391.377,
-                  "cuda_time_us": 73.08699999999999,
-                  "pct_cuda_time": 1.0061903414703315,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 30.464,
-                      "cuda_time_us": 20.704,
-                      "pct_cuda_time": 0.2850324247787123,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.704,
-                          "pct_cuda_time": 0.2850324247787123,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 118.811,
-                      "cuda_time_us": 3.84,
-                      "pct_cuda_time": 0.052865364719390226,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.84,
-                          "pct_cuda_time": 0.052865364719390226,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 176.711,
-                      "cuda_time_us": 30.174999999999997,
-                      "pct_cuda_time": 0.4154198907311458,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.336,
-                          "pct_cuda_time": 0.03215976353762905,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.807,
-                          "pct_cuda_time": 0.327751494238157,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.56,
-                          "pct_cuda_time": 0.03524357647959349,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.472,
-                          "pct_cuda_time": 0.020265056475766253,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 32.192,
-                      "cuda_time_us": 18.368,
-                      "pct_cuda_time": 0.2528726612410832,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.368,
-                          "pct_cuda_time": 0.2528726612410832,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.703,
-                  "cuda_time_us": 3.424,
-                  "pct_cuda_time": 0.047138283541456286,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.424,
-                      "pct_cuda_time": 0.047138283541456286,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 104.285,
-                  "cuda_time_us": 134.208,
-                  "pct_cuda_time": 1.8476444969426884,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 37.2,
-                      "cuda_time_us": 82.208,
-                      "pct_cuda_time": 1.1317593497009457,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 82.208,
-                          "pct_cuda_time": 1.1317593497009457,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 22.84,
-                      "cuda_time_us": 8.832,
-                      "pct_cuda_time": 0.12159033885459752,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.832,
-                          "pct_cuda_time": 0.12159033885459752,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 32.221,
-                      "cuda_time_us": 43.168,
-                      "pct_cuda_time": 0.5942948083871451,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.168,
-                          "pct_cuda_time": 0.5942948083871451,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 504.409,
-              "cuda_time_us": 215.231,
-              "pct_cuda_time": 2.96308992549976,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.327,
-                  "cuda_time_us": 3.488,
-                  "pct_cuda_time": 0.048019372953446125,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.488,
-                      "pct_cuda_time": 0.048019372953446125,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 357.289,
-                  "cuda_time_us": 72.28699999999999,
-                  "pct_cuda_time": 0.9951767238204586,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 28.483,
-                      "cuda_time_us": 20.864,
-                      "pct_cuda_time": 0.2872351483086869,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.864,
-                          "pct_cuda_time": 0.2872351483086869,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 107.246,
-                      "cuda_time_us": 3.648,
-                      "pct_cuda_time": 0.050222096483420714,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.648,
-                          "pct_cuda_time": 0.050222096483420714,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 163.445,
-                      "cuda_time_us": 29.535,
-                      "pct_cuda_time": 0.4066089966112475,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.272,
-                          "pct_cuda_time": 0.031278674125639214,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.327,
-                          "pct_cuda_time": 0.3211433236482333,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.465,
-                          "pct_cuda_time": 0.03393570938367107,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.471,
-                          "pct_cuda_time": 0.020251289453703913,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 27.529,
-                      "cuda_time_us": 18.24,
-                      "pct_cuda_time": 0.25111048241710354,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.24,
-                          "pct_cuda_time": 0.25111048241710354,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.988,
-                  "cuda_time_us": 3.328,
-                  "pct_cuda_time": 0.04581664942347153,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.328,
-                      "pct_cuda_time": 0.04581664942347153,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 96.376,
-                  "cuda_time_us": 136.12800000000001,
-                  "pct_cuda_time": 1.8740771793023838,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 33.99,
-                      "cuda_time_us": 83.488,
-                      "pct_cuda_time": 1.1493811379407426,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 83.488,
-                          "pct_cuda_time": 1.1493811379407426,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.968,
-                      "cuda_time_us": 8.736,
-                      "pct_cuda_time": 0.12026870473661277,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.736,
-                          "pct_cuda_time": 0.12026870473661277,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 29.517,
-                      "cuda_time_us": 43.904,
-                      "pct_cuda_time": 0.6044273366250283,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.904,
-                          "pct_cuda_time": 0.6044273366250283,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 502.608,
-              "cuda_time_us": 212.223,
-              "pct_cuda_time": 2.921678723136238,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.855,
-                  "cuda_time_us": 3.424,
-                  "pct_cuda_time": 0.047138283541456286,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.424,
-                      "pct_cuda_time": 0.047138283541456286,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 355.405,
-                  "cuda_time_us": 72.864,
-                  "pct_cuda_time": 1.0031202955504297,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 29.179,
-                      "cuda_time_us": 20.576,
-                      "pct_cuda_time": 0.2832702459547326,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.576,
-                          "pct_cuda_time": 0.2832702459547326,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 100.954,
-                      "cuda_time_us": 3.776,
-                      "pct_cuda_time": 0.051984275307400386,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.776,
-                          "pct_cuda_time": 0.051984275307400386,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 161.704,
-                      "cuda_time_us": 29.951999999999998,
-                      "pct_cuda_time": 0.41234984481124376,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.24,
-                          "pct_cuda_time": 0.0308381294196443,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.584,
-                          "pct_cuda_time": 0.32468144831825496,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.592,
-                          "pct_cuda_time": 0.035684121185588405,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.536,
-                          "pct_cuda_time": 0.021146145887756092,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 27.51,
-                      "cuda_time_us": 18.56,
-                      "pct_cuda_time": 0.25551592947705276,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.56,
-                          "pct_cuda_time": 0.25551592947705276,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.002,
-                  "cuda_time_us": 3.328,
-                  "pct_cuda_time": 0.04581664942347153,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.328,
-                      "pct_cuda_time": 0.04581664942347153,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 96.234,
-                  "cuda_time_us": 132.607,
-                  "pct_cuda_time": 1.8256034946208803,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.115,
-                      "cuda_time_us": 80.223,
-                      "pct_cuda_time": 1.1044318109071984,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 80.223,
-                          "pct_cuda_time": 1.1044318109071984,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.587,
-                      "cuda_time_us": 8.576,
-                      "pct_cuda_time": 0.11806598120663817,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.576,
-                          "pct_cuda_time": 0.11806598120663817,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 29.383,
-                      "cuda_time_us": 43.808,
-                      "pct_cuda_time": 0.6031057025070434,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.808,
-                          "pct_cuda_time": 0.6031057025070434,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 492.75,
-              "cuda_time_us": 211.551,
-              "pct_cuda_time": 2.9124272843103443,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.707,
-                  "cuda_time_us": 3.552,
-                  "pct_cuda_time": 0.048900462365435965,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.552,
-                      "pct_cuda_time": 0.048900462365435965,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 349.782,
-                  "cuda_time_us": 72.576,
-                  "pct_cuda_time": 0.9991553931964752,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 27.905,
-                      "cuda_time_us": 20.64,
-                      "pct_cuda_time": 0.2841513353667225,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.64,
-                          "pct_cuda_time": 0.2841513353667225,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 104.999,
-                      "cuda_time_us": 3.68,
-                      "pct_cuda_time": 0.050662641189415644,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.68,
-                          "pct_cuda_time": 0.050662641189415644,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 160.034,
-                      "cuda_time_us": 30.08,
-                      "pct_cuda_time": 0.4141120236352235,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.4,
-                          "pct_cuda_time": 0.033040852949618886,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.712,
-                          "pct_cuda_time": 0.3264436271422346,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.464,
-                          "pct_cuda_time": 0.033921942361608726,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 26.756,
-                      "cuda_time_us": 18.176,
-                      "pct_cuda_time": 0.2502293930051137,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.176,
-                          "pct_cuda_time": 0.2502293930051137,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.918,
-                  "cuda_time_us": 3.296,
-                  "pct_cuda_time": 0.04537610471747661,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.296,
-                      "pct_cuda_time": 0.04537610471747661,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 94.955,
-                  "cuda_time_us": 132.12699999999998,
-                  "pct_cuda_time": 1.8189953240309562,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 33.156,
-                      "cuda_time_us": 80.064,
-                      "pct_cuda_time": 1.1022428543992862,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 80.064,
-                          "pct_cuda_time": 1.1022428543992862,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.186,
-                      "cuda_time_us": 8.576,
-                      "pct_cuda_time": 0.11806598120663817,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.576,
-                          "pct_cuda_time": 0.11806598120663817,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 29.567,
-                      "cuda_time_us": 43.487,
-                      "pct_cuda_time": 0.598686488425032,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.487,
-                          "pct_cuda_time": 0.598686488425032,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 535.017,
-              "cuda_time_us": 211.965,
-              "pct_cuda_time": 2.9181268314441535,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 20.186,
-                  "cuda_time_us": 3.616,
-                  "pct_cuda_time": 0.049781551777425805,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.616,
-                      "pct_cuda_time": 0.049781551777425805,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 373.628,
-                  "cuda_time_us": 72.288,
-                  "pct_cuda_time": 0.995190490842521,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 28.615,
-                      "cuda_time_us": 20.64,
-                      "pct_cuda_time": 0.2841513353667225,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.64,
-                          "pct_cuda_time": 0.2841513353667225,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 100.361,
-                      "cuda_time_us": 3.776,
-                      "pct_cuda_time": 0.051984275307400386,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.776,
-                          "pct_cuda_time": 0.051984275307400386,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 175.325,
-                      "cuda_time_us": 29.568,
-                      "pct_cuda_time": 0.40706330833930476,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.24,
-                          "pct_cuda_time": 0.0308381294196443,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.296,
-                          "pct_cuda_time": 0.3207165459643007,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.528,
-                          "pct_cuda_time": 0.034803031773598565,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 30.109,
-                      "cuda_time_us": 18.304,
-                      "pct_cuda_time": 0.2519915718290934,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.304,
-                          "pct_cuda_time": 0.2519915718290934,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 18.501,
-                  "cuda_time_us": 3.328,
-                  "pct_cuda_time": 0.04581664942347153,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.328,
-                      "pct_cuda_time": 0.04581664942347153,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 99.116,
-                  "cuda_time_us": 132.733,
-                  "pct_cuda_time": 1.8273381394007353,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 36.3,
-                      "cuda_time_us": 80.447,
-                      "pct_cuda_time": 1.107515623849163,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 80.447,
-                          "pct_cuda_time": 1.107515623849163,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 22.014,
-                      "cuda_time_us": 9.151,
-                      "pct_cuda_time": 0.12598201889248437,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 9.151,
-                          "pct_cuda_time": 0.12598201889248437,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 29.411,
-                      "cuda_time_us": 43.135,
-                      "pct_cuda_time": 0.5938404966590878,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.135,
-                          "pct_cuda_time": 0.5938404966590878,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 526.821,
-              "cuda_time_us": 211.774,
-              "pct_cuda_time": 2.9154973302302465,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.021,
-                  "cuda_time_us": 3.488,
-                  "pct_cuda_time": 0.048019372953446125,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.488,
-                      "pct_cuda_time": 0.048019372953446125,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 368.943,
-                  "cuda_time_us": 72.606,
-                  "pct_cuda_time": 0.9995684038583456,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 28.847,
-                      "cuda_time_us": 20.384,
-                      "pct_cuda_time": 0.2806269777187631,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.384,
-                          "pct_cuda_time": 0.2806269777187631,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 111.361,
-                      "cuda_time_us": 3.712,
-                      "pct_cuda_time": 0.051103185895410554,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.712,
-                          "pct_cuda_time": 0.051103185895410554,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 169.301,
-                      "cuda_time_us": 29.854,
-                      "pct_cuda_time": 0.4110006766491343,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.271,
-                          "pct_cuda_time": 0.03126490710357688,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.584,
-                          "pct_cuda_time": 0.32468144831825496,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.496,
-                          "pct_cuda_time": 0.03436248706760365,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.503,
-                          "pct_cuda_time": 0.02069183415969883,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 28.865,
-                      "cuda_time_us": 18.656,
-                      "pct_cuda_time": 0.2568375635950375,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.656,
-                          "pct_cuda_time": 0.2568375635950375,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 18.283,
-                  "cuda_time_us": 3.296,
-                  "pct_cuda_time": 0.04537610471747661,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.296,
-                      "pct_cuda_time": 0.04537610471747661,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 106.243,
-                  "cuda_time_us": 132.38400000000001,
-                  "pct_cuda_time": 1.8225334487009783,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 35.521,
-                      "cuda_time_us": 80.608,
-                      "pct_cuda_time": 1.1097321144011998,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 80.608,
-                          "pct_cuda_time": 1.1097321144011998,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 27.938,
-                      "cuda_time_us": 8.64,
-                      "pct_cuda_time": 0.11894707061862803,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.64,
-                          "pct_cuda_time": 0.11894707061862803,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 31.144,
-                      "cuda_time_us": 43.136,
-                      "pct_cuda_time": 0.5938542636811502,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.136,
-                          "pct_cuda_time": 0.5938542636811502,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 515.051,
-              "cuda_time_us": 211.99800000000002,
-              "pct_cuda_time": 2.9185811431722106,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.298,
-                  "cuda_time_us": 3.873,
-                  "pct_cuda_time": 0.05331967644744749,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.873,
-                      "pct_cuda_time": 0.05331967644744749,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 367.597,
-                  "cuda_time_us": 72.31700000000001,
-                  "pct_cuda_time": 0.995589734482329,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 28.727,
-                      "cuda_time_us": 20.64,
-                      "pct_cuda_time": 0.2841513353667225,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.64,
-                          "pct_cuda_time": 0.2841513353667225,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 112.782,
-                      "cuda_time_us": 3.744,
-                      "pct_cuda_time": 0.05154373060140547,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.744,
-                          "pct_cuda_time": 0.05154373060140547,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 167.782,
-                      "cuda_time_us": 29.598000000000003,
-                      "pct_cuda_time": 0.40747631900117504,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.24,
-                          "pct_cuda_time": 0.0308381294196443,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.359,
-                          "pct_cuda_time": 0.3215838683542282,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.496,
-                          "pct_cuda_time": 0.03436248706760365,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.503,
-                          "pct_cuda_time": 0.02069183415969883,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 27.076,
-                      "cuda_time_us": 18.335,
-                      "pct_cuda_time": 0.252418349513026,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.335,
-                          "pct_cuda_time": 0.252418349513026,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.261,
-                  "cuda_time_us": 3.456,
-                  "pct_cuda_time": 0.0475788282474512,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.456,
-                      "pct_cuda_time": 0.0475788282474512,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 97.96,
-                  "cuda_time_us": 132.352,
-                  "pct_cuda_time": 1.8220929039949831,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.04,
-                      "cuda_time_us": 79.488,
-                      "pct_cuda_time": 1.0943130496913775,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.488,
-                          "pct_cuda_time": 1.0943130496913775,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.635,
-                      "cuda_time_us": 8.48,
-                      "pct_cuda_time": 0.11674434708865342,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.48,
-                          "pct_cuda_time": 0.11674434708865342,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 30.843,
-                      "cuda_time_us": 44.384,
-                      "pct_cuda_time": 0.611035507214952,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 44.384,
-                          "pct_cuda_time": 0.611035507214952,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 492.119,
-              "cuda_time_us": 211.968,
-              "pct_cuda_time": 2.91816813251034,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.119,
-                  "cuda_time_us": 3.584,
-                  "pct_cuda_time": 0.049341007071430874,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.584,
-                      "pct_cuda_time": 0.049341007071430874,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 337.822,
-                  "cuda_time_us": 72.097,
-                  "pct_cuda_time": 0.9925609896286137,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 27.866,
-                      "cuda_time_us": 20.448,
-                      "pct_cuda_time": 0.281508067130753,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.448,
-                          "pct_cuda_time": 0.281508067130753,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 100.297,
-                      "cuda_time_us": 3.585,
-                      "pct_cuda_time": 0.049354774093493224,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.585,
-                          "pct_cuda_time": 0.049354774093493224,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 154.941,
-                      "cuda_time_us": 29.951999999999998,
-                      "pct_cuda_time": 0.41234984481124376,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.304,
-                          "pct_cuda_time": 0.03171921883163414,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.552,
-                          "pct_cuda_time": 0.32424090361226005,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.592,
-                          "pct_cuda_time": 0.035684121185588405,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 25.766,
-                      "cuda_time_us": 18.112,
-                      "pct_cuda_time": 0.24934830359312388,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.112,
-                          "pct_cuda_time": 0.24934830359312388,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.425,
-                  "cuda_time_us": 3.36,
-                  "pct_cuda_time": 0.046257194129466446,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.36,
-                      "pct_cuda_time": 0.046257194129466446,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 105.429,
-                  "cuda_time_us": 132.927,
-                  "pct_cuda_time": 1.8300089416808292,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 39.223,
-                      "cuda_time_us": 80.223,
-                      "pct_cuda_time": 1.1044318109071984,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 80.223,
-                          "pct_cuda_time": 1.1044318109071984,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.616,
-                      "cuda_time_us": 8.64,
-                      "pct_cuda_time": 0.11894707061862803,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.64,
-                          "pct_cuda_time": 0.11894707061862803,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 30.197,
-                      "cuda_time_us": 44.064,
-                      "pct_cuda_time": 0.6066300601550029,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 44.064,
-                          "pct_cuda_time": 0.6066300601550029,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 515.681,
-              "cuda_time_us": 211.423,
-              "pct_cuda_time": 2.9106651054863644,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.273,
-                  "cuda_time_us": 3.552,
-                  "pct_cuda_time": 0.048900462365435965,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.552,
-                      "pct_cuda_time": 0.048900462365435965,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 370.649,
-                  "cuda_time_us": 73.055,
-                  "pct_cuda_time": 1.005749796764337,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 47.811,
-                      "cuda_time_us": 20.896,
-                      "pct_cuda_time": 0.2876756930146818,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.896,
-                          "pct_cuda_time": 0.2876756930146818,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 100.45,
-                      "cuda_time_us": 3.808,
-                      "pct_cuda_time": 0.05242482001339531,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.808,
-                          "pct_cuda_time": 0.05242482001339531,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 163.927,
-                      "cuda_time_us": 29.950999999999997,
-                      "pct_cuda_time": 0.4123360777891814,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.336,
-                          "pct_cuda_time": 0.03215976353762905,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.584,
-                          "pct_cuda_time": 0.32468144831825496,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.528,
-                          "pct_cuda_time": 0.034803031773598565,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.503,
-                          "pct_cuda_time": 0.02069183415969883,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 28.958,
-                      "cuda_time_us": 18.4,
-                      "pct_cuda_time": 0.2533132059470782,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.4,
-                          "pct_cuda_time": 0.2533132059470782,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.336,
-                  "cuda_time_us": 3.424,
-                  "pct_cuda_time": 0.047138283541456286,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.424,
-                      "pct_cuda_time": 0.047138283541456286,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 98.163,
-                  "cuda_time_us": 131.392,
-                  "pct_cuda_time": 1.8088765628151358,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 35.053,
-                      "cuda_time_us": 79.168,
-                      "pct_cuda_time": 1.0899076026314287,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.168,
-                          "pct_cuda_time": 1.0899076026314287,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.191,
-                      "cuda_time_us": 9.184,
-                      "pct_cuda_time": 0.1264363306205416,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 9.184,
-                          "pct_cuda_time": 0.1264363306205416,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 30.545,
-                      "cuda_time_us": 43.04,
-                      "pct_cuda_time": 0.5925326295631654,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.04,
-                          "pct_cuda_time": 0.5925326295631654,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 488.661,
-              "cuda_time_us": 211.67700000000002,
-              "pct_cuda_time": 2.9141619290901994,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.692,
-                  "cuda_time_us": 3.616,
-                  "pct_cuda_time": 0.049781551777425805,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.616,
-                      "pct_cuda_time": 0.049781551777425805,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 341.136,
-                  "cuda_time_us": 72.381,
-                  "pct_cuda_time": 0.9964708238943187,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 29.736,
-                      "cuda_time_us": 20.671,
-                      "pct_cuda_time": 0.28457811305065506,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.671,
-                          "pct_cuda_time": 0.28457811305065506,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 100.335,
-                      "cuda_time_us": 3.648,
-                      "pct_cuda_time": 0.050222096483420714,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.648,
-                          "pct_cuda_time": 0.050222096483420714,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 154.053,
-                      "cuda_time_us": 29.854999999999997,
-                      "pct_cuda_time": 0.41101444367119666,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.336,
-                          "pct_cuda_time": 0.03215976353762905,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.423,
-                          "pct_cuda_time": 0.32246495776621803,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.592,
-                          "pct_cuda_time": 0.035684121185588405,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 27.12,
-                      "cuda_time_us": 18.207,
-                      "pct_cuda_time": 0.25065617068904633,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.207,
-                          "pct_cuda_time": 0.25065617068904633,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.955,
-                  "cuda_time_us": 3.457,
-                  "pct_cuda_time": 0.047592595269513545,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.457,
-                      "pct_cuda_time": 0.047592595269513545,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 101.799,
-                  "cuda_time_us": 132.223,
-                  "pct_cuda_time": 1.8203169581489413,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 33.565,
-                      "cuda_time_us": 79.103,
-                      "pct_cuda_time": 1.0890127461973762,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.103,
-                          "pct_cuda_time": 1.0890127461973762,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.375,
-                      "cuda_time_us": 9.536,
-                      "pct_cuda_time": 0.13128232238648574,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 9.536,
-                          "pct_cuda_time": 0.13128232238648574,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 29.177,
-                      "cuda_time_us": 43.584,
-                      "pct_cuda_time": 0.6000218895650791,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.584,
-                          "pct_cuda_time": 0.6000218895650791,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 504.236,
-              "cuda_time_us": 212.47899999999998,
-              "pct_cuda_time": 2.9252030807841964,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.166,
-                  "cuda_time_us": 3.456,
-                  "pct_cuda_time": 0.0475788282474512,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.456,
-                      "pct_cuda_time": 0.0475788282474512,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 366.506,
-                  "cuda_time_us": 73.087,
-                  "pct_cuda_time": 1.0061903414703317,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 27.856,
-                      "cuda_time_us": 20.896,
-                      "pct_cuda_time": 0.2876756930146818,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.896,
-                          "pct_cuda_time": 0.2876756930146818,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 96.48,
-                      "cuda_time_us": 3.968,
-                      "pct_cuda_time": 0.0546275435433699,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.968,
-                          "pct_cuda_time": 0.0546275435433699,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 157.563,
-                      "cuda_time_us": 29.791,
-                      "pct_cuda_time": 0.41013335425920683,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.24,
-                          "pct_cuda_time": 0.0308381294196443,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.519,
-                          "pct_cuda_time": 0.3237865918842028,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.528,
-                          "pct_cuda_time": 0.034803031773598565,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 26.931,
-                      "cuda_time_us": 18.432,
-                      "pct_cuda_time": 0.2537537506530731,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.432,
-                          "pct_cuda_time": 0.2537537506530731,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.794,
-                  "cuda_time_us": 3.296,
-                  "pct_cuda_time": 0.04537610471747661,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.296,
-                      "pct_cuda_time": 0.04537610471747661,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 93.713,
-                  "cuda_time_us": 132.64,
-                  "pct_cuda_time": 1.8260578063489372,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 33.361,
-                      "cuda_time_us": 79.744,
-                      "pct_cuda_time": 1.097837407339337,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.744,
-                          "pct_cuda_time": 1.097837407339337,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.409,
-                      "cuda_time_us": 9.184,
-                      "pct_cuda_time": 0.1264363306205416,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 9.184,
-                          "pct_cuda_time": 0.1264363306205416,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 28.215,
-                      "cuda_time_us": 43.712,
-                      "pct_cuda_time": 0.6017840683890588,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.712,
-                          "pct_cuda_time": 0.6017840683890588,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 562.581,
-              "cuda_time_us": 212.222,
-              "pct_cuda_time": 2.921664956114175,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 13.867,
-                  "cuda_time_us": 3.584,
-                  "pct_cuda_time": 0.049341007071430874,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.584,
-                      "pct_cuda_time": 0.049341007071430874,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 410.087,
-                  "cuda_time_us": 72.224,
-                  "pct_cuda_time": 0.9943094014305311,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 27.725,
-                      "cuda_time_us": 20.32,
-                      "pct_cuda_time": 0.27974588830677327,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.32,
-                          "pct_cuda_time": 0.27974588830677327,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 99.087,
-                      "cuda_time_us": 3.68,
-                      "pct_cuda_time": 0.050662641189415644,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.68,
-                          "pct_cuda_time": 0.050662641189415644,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 221.741,
-                      "cuda_time_us": 30.048,
-                      "pct_cuda_time": 0.4136714789292285,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.304,
-                          "pct_cuda_time": 0.03171921883163414,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.776,
-                          "pct_cuda_time": 0.32732471655422446,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.496,
-                          "pct_cuda_time": 0.03436248706760365,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.472,
-                          "pct_cuda_time": 0.020265056475766253,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 32.57,
-                      "cuda_time_us": 18.176,
-                      "pct_cuda_time": 0.2502293930051137,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.176,
-                          "pct_cuda_time": 0.2502293930051137,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 18.777,
-                  "cuda_time_us": 3.359,
-                  "pct_cuda_time": 0.0462434271074041,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.359,
-                      "pct_cuda_time": 0.0462434271074041,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 104.151,
-                  "cuda_time_us": 133.055,
-                  "pct_cuda_time": 1.831771120504809,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 38.339,
-                      "cuda_time_us": 80.255,
-                      "pct_cuda_time": 1.1048723556131934,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 80.255,
-                          "pct_cuda_time": 1.1048723556131934,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 22.971,
-                      "cuda_time_us": 8.832,
-                      "pct_cuda_time": 0.12159033885459752,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.832,
-                          "pct_cuda_time": 0.12159033885459752,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 30.502,
-                      "cuda_time_us": 43.968,
-                      "pct_cuda_time": 0.6053084260370182,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.968,
-                          "pct_cuda_time": 0.6053084260370182,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 496.491,
-              "cuda_time_us": 211.647,
-              "pct_cuda_time": 2.913748918428329,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.653,
-                  "cuda_time_us": 3.424,
-                  "pct_cuda_time": 0.047138283541456286,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.424,
-                      "pct_cuda_time": 0.047138283541456286,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 352.754,
-                  "cuda_time_us": 72.896,
-                  "pct_cuda_time": 1.0035608402564244,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 27.996,
-                      "cuda_time_us": 20.8,
-                      "pct_cuda_time": 0.2863540588966971,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.8,
-                          "pct_cuda_time": 0.2863540588966971,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 101.387,
-                      "cuda_time_us": 3.776,
-                      "pct_cuda_time": 0.051984275307400386,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.776,
-                          "pct_cuda_time": 0.051984275307400386,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 166.705,
-                      "cuda_time_us": 30.112,
-                      "pct_cuda_time": 0.41455256834121834,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.368,
-                          "pct_cuda_time": 0.03260030824362397,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.552,
-                          "pct_cuda_time": 0.32424090361226005,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.688,
-                          "pct_cuda_time": 0.03700575530357316,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 26.815,
-                      "cuda_time_us": 18.208,
-                      "pct_cuda_time": 0.2506699377111087,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.208,
-                          "pct_cuda_time": 0.2506699377111087,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.722,
-                  "cuda_time_us": 3.488,
-                  "pct_cuda_time": 0.048019372953446125,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.488,
-                      "pct_cuda_time": 0.048019372953446125,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 97.186,
-                  "cuda_time_us": 131.839,
-                  "pct_cuda_time": 1.8150304216770021,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.137,
-                      "cuda_time_us": 79.423,
-                      "pct_cuda_time": 1.0934181932573255,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.423,
-                          "pct_cuda_time": 1.0934181932573255,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.796,
-                      "cuda_time_us": 8.833,
-                      "pct_cuda_time": 0.12160410587665987,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.833,
-                          "pct_cuda_time": 0.12160410587665987,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 29.97,
-                      "cuda_time_us": 43.583,
-                      "pct_cuda_time": 0.6000081225430167,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.583,
-                          "pct_cuda_time": 0.6000081225430167,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 507.974,
-              "cuda_time_us": 210.56199999999998,
-              "pct_cuda_time": 2.8988116994906887,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.439,
-                  "cuda_time_us": 3.52,
-                  "pct_cuda_time": 0.04845991765944104,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.52,
-                      "pct_cuda_time": 0.04845991765944104,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 358.786,
-                  "cuda_time_us": 72.226,
-                  "pct_cuda_time": 0.9943369354746558,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 27.451,
-                      "cuda_time_us": 20.64,
-                      "pct_cuda_time": 0.2841513353667225,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.64,
-                          "pct_cuda_time": 0.2841513353667225,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 98.135,
-                      "cuda_time_us": 3.744,
-                      "pct_cuda_time": 0.05154373060140547,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.744,
-                          "pct_cuda_time": 0.05154373060140547,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 170.858,
-                      "cuda_time_us": 29.889999999999997,
-                      "pct_cuda_time": 0.41149628944337857,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.304,
-                          "pct_cuda_time": 0.03171921883163414,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.585,
-                          "pct_cuda_time": 0.32469521534031737,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.496,
-                          "pct_cuda_time": 0.03436248706760365,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.505,
-                          "pct_cuda_time": 0.020719368203823512,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 29.27,
-                      "cuda_time_us": 17.952,
-                      "pct_cuda_time": 0.24714558006314935,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 17.952,
-                          "pct_cuda_time": 0.24714558006314935,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.893,
-                  "cuda_time_us": 3.36,
-                  "pct_cuda_time": 0.046257194129466446,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.36,
-                      "pct_cuda_time": 0.046257194129466446,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 101.54,
-                  "cuda_time_us": 131.456,
-                  "pct_cuda_time": 1.809757652227125,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 36.58,
-                      "cuda_time_us": 79.264,
-                      "pct_cuda_time": 1.0912292367494132,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.264,
-                          "pct_cuda_time": 1.0912292367494132,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.923,
-                      "cuda_time_us": 9.216,
-                      "pct_cuda_time": 0.12687687532653655,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 9.216,
-                          "pct_cuda_time": 0.12687687532653655,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 31.568,
-                      "cuda_time_us": 42.976,
-                      "pct_cuda_time": 0.5916515401511756,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 42.976,
-                          "pct_cuda_time": 0.5916515401511756,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 499.84,
-              "cuda_time_us": 211.933,
-              "pct_cuda_time": 2.9176862867381583,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.661,
-                  "cuda_time_us": 3.52,
-                  "pct_cuda_time": 0.04845991765944104,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.52,
-                      "pct_cuda_time": 0.04845991765944104,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 359.251,
-                  "cuda_time_us": 73.086,
-                  "pct_cuda_time": 1.0061765744482694,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 28.694,
-                      "cuda_time_us": 20.8,
-                      "pct_cuda_time": 0.2863540588966971,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.8,
-                          "pct_cuda_time": 0.2863540588966971,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 110.097,
-                      "cuda_time_us": 3.712,
-                      "pct_cuda_time": 0.051103185895410554,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.712,
-                          "pct_cuda_time": 0.051103185895410554,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 163.835,
-                      "cuda_time_us": 30.078999999999997,
-                      "pct_cuda_time": 0.4140982566131611,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.24,
-                          "pct_cuda_time": 0.0308381294196443,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.615,
-                          "pct_cuda_time": 0.32510822600218753,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.72,
-                          "pct_cuda_time": 0.03744630000956808,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 27.002,
-                      "cuda_time_us": 18.495,
-                      "pct_cuda_time": 0.25462107304300063,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.495,
-                          "pct_cuda_time": 0.25462107304300063,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.287,
-                  "cuda_time_us": 3.52,
-                  "pct_cuda_time": 0.04845991765944104,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.52,
-                      "pct_cuda_time": 0.04845991765944104,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 92.025,
-                  "cuda_time_us": 131.80700000000002,
-                  "pct_cuda_time": 1.8145898769710074,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 32.008,
-                      "cuda_time_us": 79.775,
-                      "pct_cuda_time": 1.0982641850232697,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.775,
-                          "pct_cuda_time": 1.0982641850232697,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.151,
-                      "cuda_time_us": 8.576,
-                      "pct_cuda_time": 0.11806598120663817,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.576,
-                          "pct_cuda_time": 0.11806598120663817,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 29.545,
-                      "cuda_time_us": 43.456,
-                      "pct_cuda_time": 0.5982597107410994,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.456,
-                          "pct_cuda_time": 0.5982597107410994,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 472.827,
-              "cuda_time_us": 211.77700000000002,
-              "pct_cuda_time": 2.9155386312964335,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 13.771,
-                  "cuda_time_us": 3.52,
-                  "pct_cuda_time": 0.04845991765944104,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.52,
-                      "pct_cuda_time": 0.04845991765944104,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 336.553,
-                  "cuda_time_us": 72.929,
-                  "pct_cuda_time": 1.0040151519844818,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 27.469,
-                      "cuda_time_us": 20.736,
-                      "pct_cuda_time": 0.28547296948470724,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.736,
-                          "pct_cuda_time": 0.28547296948470724,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 96.158,
-                      "cuda_time_us": 3.872,
-                      "pct_cuda_time": 0.05330590942538515,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.872,
-                          "pct_cuda_time": 0.05330590942538515,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 158.534,
-                      "cuda_time_us": 29.857,
-                      "pct_cuda_time": 0.41104197771532136,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.305,
-                          "pct_cuda_time": 0.03173298585369648,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.584,
-                          "pct_cuda_time": 0.32468144831825496,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.496,
-                          "pct_cuda_time": 0.03436248706760365,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.472,
-                          "pct_cuda_time": 0.020265056475766253,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 26.554,
-                      "cuda_time_us": 18.464,
-                      "pct_cuda_time": 0.25419429535906796,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.464,
-                          "pct_cuda_time": 0.25419429535906796,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.557,
-                  "cuda_time_us": 3.36,
-                  "pct_cuda_time": 0.046257194129466446,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.36,
-                      "pct_cuda_time": 0.046257194129466446,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 90.748,
-                  "cuda_time_us": 131.96800000000002,
-                  "pct_cuda_time": 1.8168063675230444,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 31.906,
-                      "cuda_time_us": 79.808,
-                      "pct_cuda_time": 1.098718496751327,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.808,
-                          "pct_cuda_time": 1.098718496751327,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.123,
-                      "cuda_time_us": 8.607,
-                      "pct_cuda_time": 0.11849275889057075,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.607,
-                          "pct_cuda_time": 0.11849275889057075,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 27.978,
-                      "cuda_time_us": 43.553,
-                      "pct_cuda_time": 0.5995951118811464,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.553,
-                          "pct_cuda_time": 0.5995951118811464,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 465.851,
-              "cuda_time_us": 212.09299999999996,
-              "pct_cuda_time": 2.9198890102681325,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 13.815,
-                  "cuda_time_us": 3.615,
-                  "pct_cuda_time": 0.049767784755363455,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.615,
-                      "pct_cuda_time": 0.049767784755363455,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 327.601,
-                  "cuda_time_us": 72.606,
-                  "pct_cuda_time": 0.9995684038583456,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 28.067,
-                      "cuda_time_us": 20.448,
-                      "pct_cuda_time": 0.281508067130753,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.448,
-                          "pct_cuda_time": 0.281508067130753,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 95.273,
-                      "cuda_time_us": 3.776,
-                      "pct_cuda_time": 0.051984275307400386,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.776,
-                          "pct_cuda_time": 0.051984275307400386,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 150.169,
-                      "cuda_time_us": 30.207,
-                      "pct_cuda_time": 0.4158604354371408,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.336,
-                          "pct_cuda_time": 0.03215976353762905,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.68,
-                          "pct_cuda_time": 0.32600308243623977,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.687,
-                          "pct_cuda_time": 0.03699198828151082,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 25.891,
-                      "cuda_time_us": 18.175,
-                      "pct_cuda_time": 0.2502156259830514,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.175,
-                          "pct_cuda_time": 0.2502156259830514,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.621,
-                  "cuda_time_us": 3.328,
-                  "pct_cuda_time": 0.04581664942347153,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.328,
-                      "pct_cuda_time": 0.04581664942347153,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 93.178,
-                  "cuda_time_us": 132.54399999999998,
-                  "pct_cuda_time": 1.8247361722309525,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 32.669,
-                      "cuda_time_us": 80.0,
-                      "pct_cuda_time": 1.1013617649872964,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 80.0,
-                          "pct_cuda_time": 1.1013617649872964,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.37,
-                      "cuda_time_us": 8.576,
-                      "pct_cuda_time": 0.11806598120663817,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.576,
-                          "pct_cuda_time": 0.11806598120663817,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 28.872,
-                      "cuda_time_us": 43.968,
-                      "pct_cuda_time": 0.6053084260370182,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.968,
-                          "pct_cuda_time": 0.6053084260370182,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 499.384,
-              "cuda_time_us": 211.425,
-              "pct_cuda_time": 2.9106926395304895,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.364,
-                  "cuda_time_us": 3.424,
-                  "pct_cuda_time": 0.047138283541456286,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.424,
-                      "pct_cuda_time": 0.047138283541456286,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 359.791,
-                  "cuda_time_us": 71.937,
-                  "pct_cuda_time": 0.9903582660986392,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 28.858,
-                      "cuda_time_us": 20.383,
-                      "pct_cuda_time": 0.28061321069670075,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.383,
-                          "pct_cuda_time": 0.28061321069670075,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 101.205,
-                      "cuda_time_us": 3.616,
-                      "pct_cuda_time": 0.049781551777425805,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.616,
-                          "pct_cuda_time": 0.049781551777425805,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 172.066,
-                      "cuda_time_us": 29.698,
-                      "pct_cuda_time": 0.4088530212074091,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.336,
-                          "pct_cuda_time": 0.03215976353762905,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.425,
-                          "pct_cuda_time": 0.32249249181034273,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.465,
-                          "pct_cuda_time": 0.03393570938367107,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.472,
-                          "pct_cuda_time": 0.020265056475766253,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 27.625,
-                      "cuda_time_us": 18.24,
-                      "pct_cuda_time": 0.25111048241710354,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.24,
-                          "pct_cuda_time": 0.25111048241710354,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.23,
-                  "cuda_time_us": 3.328,
-                  "pct_cuda_time": 0.04581664942347153,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.328,
-                      "pct_cuda_time": 0.04581664942347153,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 94.501,
-                  "cuda_time_us": 132.73600000000002,
-                  "pct_cuda_time": 1.8273794404669226,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 33.611,
-                      "cuda_time_us": 80.128,
-                      "pct_cuda_time": 1.103123943811276,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 80.128,
-                          "pct_cuda_time": 1.103123943811276,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.036,
-                      "cuda_time_us": 8.832,
-                      "pct_cuda_time": 0.12159033885459752,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.832,
-                          "pct_cuda_time": 0.12159033885459752,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 28.716,
-                      "cuda_time_us": 43.776,
-                      "pct_cuda_time": 0.6026651578010487,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.776,
-                          "pct_cuda_time": 0.6026651578010487,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 562.585,
-              "cuda_time_us": 211.138,
-              "pct_cuda_time": 2.9067415041985973,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.004,
-                  "cuda_time_us": 3.392,
-                  "pct_cuda_time": 0.04669773883546136,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.392,
-                      "pct_cuda_time": 0.04669773883546136,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 422.281,
-                  "cuda_time_us": 73.05799999999999,
-                  "pct_cuda_time": 1.0057910978305238,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 28.108,
-                      "cuda_time_us": 20.64,
-                      "pct_cuda_time": 0.2841513353667225,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.64,
-                          "pct_cuda_time": 0.2841513353667225,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 103.573,
-                      "cuda_time_us": 3.936,
-                      "pct_cuda_time": 0.05418699883737499,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.936,
-                          "pct_cuda_time": 0.05418699883737499,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 233.512,
-                      "cuda_time_us": 29.889999999999997,
-                      "pct_cuda_time": 0.41149628944337857,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.24,
-                          "pct_cuda_time": 0.0308381294196443,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.648,
-                          "pct_cuda_time": 0.32556253773024485,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.497,
-                          "pct_cuda_time": 0.034376254089665985,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.505,
-                          "pct_cuda_time": 0.020719368203823512,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 28.396,
-                      "cuda_time_us": 18.592,
-                      "pct_cuda_time": 0.2559564741830477,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.592,
-                          "pct_cuda_time": 0.2559564741830477,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.499,
-                  "cuda_time_us": 3.328,
-                  "pct_cuda_time": 0.04581664942347153,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.328,
-                      "pct_cuda_time": 0.04581664942347153,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 94.996,
-                  "cuda_time_us": 131.36,
-                  "pct_cuda_time": 1.808436018109141,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.486,
-                      "cuda_time_us": 79.648,
-                      "pct_cuda_time": 1.0965157732213522,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.648,
-                          "pct_cuda_time": 1.0965157732213522,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.3,
-                      "cuda_time_us": 8.512,
-                      "pct_cuda_time": 0.11718489179464835,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.512,
-                          "pct_cuda_time": 0.11718489179464835,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 28.743,
-                      "cuda_time_us": 43.2,
-                      "pct_cuda_time": 0.5947353530931401,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.2,
-                          "pct_cuda_time": 0.5947353530931401,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 494.003,
-              "cuda_time_us": 212.735,
-              "pct_cuda_time": 2.928727438432156,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 13.805,
-                  "cuda_time_us": 3.616,
-                  "pct_cuda_time": 0.049781551777425805,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.616,
-                      "pct_cuda_time": 0.049781551777425805,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 351.103,
-                  "cuda_time_us": 74.239,
-                  "pct_cuda_time": 1.0220499508861487,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 26.62,
-                      "cuda_time_us": 21.408,
-                      "pct_cuda_time": 0.29472440831060054,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 21.408,
-                          "pct_cuda_time": 0.29472440831060054,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 98.807,
-                      "cuda_time_us": 3.615,
-                      "pct_cuda_time": 0.049767784755363455,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.615,
-                          "pct_cuda_time": 0.049767784755363455,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 168.468,
-                      "cuda_time_us": 29.983999999999998,
-                      "pct_cuda_time": 0.4127903895172386,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.304,
-                          "pct_cuda_time": 0.03171921883163414,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.456,
-                          "pct_cuda_time": 0.3229192694942753,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.72,
-                          "pct_cuda_time": 0.03744630000956808,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 28.851,
-                      "cuda_time_us": 19.232,
-                      "pct_cuda_time": 0.26476736830294606,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 19.232,
-                          "pct_cuda_time": 0.26476736830294606,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 17.192,
-                  "cuda_time_us": 3.328,
-                  "pct_cuda_time": 0.04581664942347153,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.328,
-                      "pct_cuda_time": 0.04581664942347153,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 97.399,
-                  "cuda_time_us": 131.55200000000002,
-                  "pct_cuda_time": 1.8110792863451106,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 35.901,
-                      "cuda_time_us": 79.712,
-                      "pct_cuda_time": 1.0973968626333421,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.712,
-                          "pct_cuda_time": 1.0973968626333421,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.941,
-                      "cuda_time_us": 8.64,
-                      "pct_cuda_time": 0.11894707061862803,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.64,
-                          "pct_cuda_time": 0.11894707061862803,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 29.163,
-                      "cuda_time_us": 43.2,
-                      "pct_cuda_time": 0.5947353530931401,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.2,
-                          "pct_cuda_time": 0.5947353530931401,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 511.068,
-              "cuda_time_us": 213.28099999999998,
-              "pct_cuda_time": 2.9362442324781943,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.925,
-                  "cuda_time_us": 3.776,
-                  "pct_cuda_time": 0.051984275307400386,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.776,
-                      "pct_cuda_time": 0.051984275307400386,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 369.334,
-                  "cuda_time_us": 73.69699999999999,
-                  "pct_cuda_time": 1.0145882249283595,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 27.647,
-                      "cuda_time_us": 21.6,
-                      "pct_cuda_time": 0.29736767654657004,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 21.6,
-                          "pct_cuda_time": 0.29736767654657004,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 118.266,
-                      "cuda_time_us": 3.776,
-                      "pct_cuda_time": 0.051984275307400386,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.776,
-                          "pct_cuda_time": 0.051984275307400386,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 165.676,
-                      "cuda_time_us": 29.824999999999996,
-                      "pct_cuda_time": 0.41060143300932644,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.24,
-                          "pct_cuda_time": 0.0308381294196443,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.52,
-                          "pct_cuda_time": 0.32380035890626513,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.592,
-                          "pct_cuda_time": 0.035684121185588405,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.473,
-                          "pct_cuda_time": 0.020278823497828596,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 27.38,
-                      "cuda_time_us": 18.496,
-                      "pct_cuda_time": 0.2546348400650629,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.496,
-                          "pct_cuda_time": 0.2546348400650629,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.391,
-                  "cuda_time_us": 3.328,
-                  "pct_cuda_time": 0.04581664942347153,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.328,
-                      "pct_cuda_time": 0.04581664942347153,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 95.509,
-                  "cuda_time_us": 132.48,
-                  "pct_cuda_time": 1.8238550828189628,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 33.995,
-                      "cuda_time_us": 80.288,
-                      "pct_cuda_time": 1.1053266673412505,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 80.288,
-                          "pct_cuda_time": 1.1053266673412505,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.668,
-                      "cuda_time_us": 8.64,
-                      "pct_cuda_time": 0.11894707061862803,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.64,
-                          "pct_cuda_time": 0.11894707061862803,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 29.672,
-                      "cuda_time_us": 43.552,
-                      "pct_cuda_time": 0.5995813448590842,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.552,
-                          "pct_cuda_time": 0.5995813448590842,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 541.273,
-              "cuda_time_us": 211.26,
-              "pct_cuda_time": 2.9084210808902027,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.488,
-                  "cuda_time_us": 3.456,
-                  "pct_cuda_time": 0.0475788282474512,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.456,
-                      "pct_cuda_time": 0.0475788282474512,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 385.782,
-                  "cuda_time_us": 72.733,
-                  "pct_cuda_time": 1.001316815660263,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 28.487,
-                      "cuda_time_us": 20.352,
-                      "pct_cuda_time": 0.2801864330127682,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.352,
-                          "pct_cuda_time": 0.2801864330127682,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 112.447,
-                      "cuda_time_us": 3.616,
-                      "pct_cuda_time": 0.049781551777425805,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.616,
-                          "pct_cuda_time": 0.049781551777425805,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 177.292,
-                      "cuda_time_us": 30.43,
-                      "pct_cuda_time": 0.41893048135704286,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.656,
-                          "pct_cuda_time": 0.03656521059757824,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.775,
-                          "pct_cuda_time": 0.3273109495321621,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.495,
-                          "pct_cuda_time": 0.034348720045541306,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 37.39,
-                      "cuda_time_us": 18.335,
-                      "pct_cuda_time": 0.252418349513026,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.335,
-                          "pct_cuda_time": 0.252418349513026,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 19.206,
-                  "cuda_time_us": 3.423,
-                  "pct_cuda_time": 0.04712451651939394,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.423,
-                      "pct_cuda_time": 0.04712451651939394,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 105.583,
-                  "cuda_time_us": 131.648,
-                  "pct_cuda_time": 1.8124009204630949,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 37.715,
-                      "cuda_time_us": 79.2,
-                      "pct_cuda_time": 1.0903481473374235,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.2,
-                          "pct_cuda_time": 1.0903481473374235,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 22.512,
-                      "cuda_time_us": 9.6,
-                      "pct_cuda_time": 0.13216341179847554,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 9.6,
-                          "pct_cuda_time": 0.13216341179847554,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 32.204,
-                      "cuda_time_us": 42.848,
-                      "pct_cuda_time": 0.5898893613271959,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 42.848,
-                          "pct_cuda_time": 0.5898893613271959,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 515.543,
-              "cuda_time_us": 211.70800000000003,
-              "pct_cuda_time": 2.9145887067741323,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.087,
-                  "cuda_time_us": 3.36,
-                  "pct_cuda_time": 0.046257194129466446,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.36,
-                      "pct_cuda_time": 0.046257194129466446,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 370.764,
-                  "cuda_time_us": 72.893,
-                  "pct_cuda_time": 1.0035195391902376,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 31.42,
-                      "cuda_time_us": 20.703,
-                      "pct_cuda_time": 0.28501865775665,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.703,
-                          "pct_cuda_time": 0.28501865775665,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 109.206,
-                      "cuda_time_us": 3.968,
-                      "pct_cuda_time": 0.0546275435433699,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.968,
-                          "pct_cuda_time": 0.0546275435433699,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 169.081,
-                      "cuda_time_us": 29.726999999999997,
-                      "pct_cuda_time": 0.40925226484721694,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.24,
-                          "pct_cuda_time": 0.0308381294196443,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.423,
-                          "pct_cuda_time": 0.32246495776621803,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.56,
-                          "pct_cuda_time": 0.03524357647959349,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 29.092,
-                      "cuda_time_us": 18.495,
-                      "pct_cuda_time": 0.25462107304300063,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.495,
-                          "pct_cuda_time": 0.25462107304300063,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 18.174,
-                  "cuda_time_us": 3.328,
-                  "pct_cuda_time": 0.04581664942347153,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.328,
-                      "pct_cuda_time": 0.04581664942347153,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 94.46,
-                  "cuda_time_us": 132.127,
-                  "pct_cuda_time": 1.8189953240309567,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 32.892,
-                      "cuda_time_us": 79.487,
-                      "pct_cuda_time": 1.0942992826693154,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.487,
-                          "pct_cuda_time": 1.0942992826693154,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.915,
-                      "cuda_time_us": 8.8,
-                      "pct_cuda_time": 0.12114979414860261,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.8,
-                          "pct_cuda_time": 0.12114979414860261,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 29.121,
-                      "cuda_time_us": 43.84,
-                      "pct_cuda_time": 0.6035462472130384,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.84,
-                          "pct_cuda_time": 0.6035462472130384,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 480.118,
-              "cuda_time_us": 211.74400000000003,
-              "pct_cuda_time": 2.9150843195683764,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.279,
-                  "cuda_time_us": 3.488,
-                  "pct_cuda_time": 0.048019372953446125,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.488,
-                      "pct_cuda_time": 0.048019372953446125,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 342.387,
-                  "cuda_time_us": 72.063,
-                  "pct_cuda_time": 0.9920929108784943,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 28.534,
-                      "cuda_time_us": 20.416,
-                      "pct_cuda_time": 0.281067522424758,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.416,
-                          "pct_cuda_time": 0.281067522424758,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 103.099,
-                      "cuda_time_us": 3.84,
-                      "pct_cuda_time": 0.052865364719390226,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.84,
-                          "pct_cuda_time": 0.052865364719390226,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 155.056,
-                      "cuda_time_us": 29.759,
-                      "pct_cuda_time": 0.4096928095532119,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.464,
-                          "pct_cuda_time": 0.033921942361608726,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.263,
-                          "pct_cuda_time": 0.3202622342362435,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.56,
-                          "pct_cuda_time": 0.03524357647959349,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.472,
-                          "pct_cuda_time": 0.020265056475766253,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 27.424,
-                      "cuda_time_us": 18.048,
-                      "pct_cuda_time": 0.24846721418113402,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.048,
-                          "pct_cuda_time": 0.24846721418113402,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.258,
-                  "cuda_time_us": 3.297,
-                  "pct_cuda_time": 0.045389871739538956,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.297,
-                      "pct_cuda_time": 0.045389871739538956,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 93.337,
-                  "cuda_time_us": 132.89600000000002,
-                  "pct_cuda_time": 1.829582163996897,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 32.284,
-                      "cuda_time_us": 80.288,
-                      "pct_cuda_time": 1.1053266673412505,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 80.288,
-                          "pct_cuda_time": 1.1053266673412505,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.636,
-                      "cuda_time_us": 8.608,
-                      "pct_cuda_time": 0.1185065259126331,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.608,
-                          "pct_cuda_time": 0.1185065259126331,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 28.066,
-                      "cuda_time_us": 44.0,
-                      "pct_cuda_time": 0.605748970743013,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 44.0,
-                          "pct_cuda_time": 0.605748970743013,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 481.054,
-              "cuda_time_us": 210.942,
-              "pct_cuda_time": 2.9040431678743786,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.208,
-                  "cuda_time_us": 3.584,
-                  "pct_cuda_time": 0.049341007071430874,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.584,
-                      "pct_cuda_time": 0.049341007071430874,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 337.538,
-                  "cuda_time_us": 72.672,
-                  "pct_cuda_time": 1.00047702731446,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 27.816,
-                      "cuda_time_us": 20.896,
-                      "pct_cuda_time": 0.2876756930146818,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.896,
-                          "pct_cuda_time": 0.2876756930146818,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 96.11,
-                      "cuda_time_us": 3.744,
-                      "pct_cuda_time": 0.05154373060140547,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.744,
-                          "pct_cuda_time": 0.05154373060140547,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 157.108,
-                      "cuda_time_us": 29.696,
-                      "pct_cuda_time": 0.40882548716328443,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.24,
-                          "pct_cuda_time": 0.0308381294196443,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.488,
-                          "pct_cuda_time": 0.3233598142002702,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.464,
-                          "pct_cuda_time": 0.033921942361608726,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 27.663,
-                      "cuda_time_us": 18.336,
-                      "pct_cuda_time": 0.2524321165350883,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.336,
-                          "pct_cuda_time": 0.2524321165350883,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.857,
-                  "cuda_time_us": 3.264,
-                  "pct_cuda_time": 0.04493556001148169,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.264,
-                      "pct_cuda_time": 0.04493556001148169,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 97.212,
-                  "cuda_time_us": 131.422,
-                  "pct_cuda_time": 1.8092895734770058,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.644,
-                      "cuda_time_us": 79.775,
-                      "pct_cuda_time": 1.0982641850232697,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.775,
-                          "pct_cuda_time": 1.0982641850232697,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.397,
-                      "cuda_time_us": 8.896,
-                      "pct_cuda_time": 0.12247142826658738,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.896,
-                          "pct_cuda_time": 0.12247142826658738,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 29.535,
-                      "cuda_time_us": 42.751,
-                      "pct_cuda_time": 0.5885539601871488,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 42.751,
-                          "pct_cuda_time": 0.5885539601871488,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 565.151,
-              "cuda_time_us": 210.784,
-              "pct_cuda_time": 2.9018679783885286,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.256,
-                  "cuda_time_us": 3.616,
-                  "pct_cuda_time": 0.049781551777425805,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.616,
-                      "pct_cuda_time": 0.049781551777425805,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 414.819,
-                  "cuda_time_us": 72.16,
-                  "pct_cuda_time": 0.9934283120185412,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 28.788,
-                      "cuda_time_us": 20.448,
-                      "pct_cuda_time": 0.281508067130753,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.448,
-                          "pct_cuda_time": 0.281508067130753,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 110.451,
-                      "cuda_time_us": 3.68,
-                      "pct_cuda_time": 0.050662641189415644,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.68,
-                          "pct_cuda_time": 0.050662641189415644,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 215.644,
-                      "cuda_time_us": 29.759999999999998,
-                      "pct_cuda_time": 0.4097065765752742,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.496,
-                          "pct_cuda_time": 0.03436248706760365,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.136,
-                          "pct_cuda_time": 0.31851382243432613,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.464,
-                          "pct_cuda_time": 0.033921942361608726,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.664,
-                          "pct_cuda_time": 0.022908324711735765,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 29.573,
-                      "cuda_time_us": 18.272,
-                      "pct_cuda_time": 0.25155102712309846,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.272,
-                          "pct_cuda_time": 0.25155102712309846,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.856,
-                  "cuda_time_us": 3.36,
-                  "pct_cuda_time": 0.046257194129466446,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.36,
-                      "pct_cuda_time": 0.046257194129466446,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 105.03,
-                  "cuda_time_us": 131.648,
-                  "pct_cuda_time": 1.8124009204630949,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 40.125,
-                      "cuda_time_us": 79.84,
-                      "pct_cuda_time": 1.0991590414573218,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.84,
-                          "pct_cuda_time": 1.0991590414573218,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.768,
-                      "cuda_time_us": 8.8,
-                      "pct_cuda_time": 0.12114979414860261,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.8,
-                          "pct_cuda_time": 0.12114979414860261,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 32.112,
-                      "cuda_time_us": 43.008,
-                      "pct_cuda_time": 0.5920920848571706,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.008,
-                          "pct_cuda_time": 0.5920920848571706,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 484.206,
-              "cuda_time_us": 211.551,
-              "pct_cuda_time": 2.9124272843103443,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.696,
-                  "cuda_time_us": 3.488,
-                  "pct_cuda_time": 0.048019372953446125,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.488,
-                      "pct_cuda_time": 0.048019372953446125,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 343.371,
-                  "cuda_time_us": 72.83099999999999,
-                  "pct_cuda_time": 1.0026659838223722,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 33.056,
-                      "cuda_time_us": 20.704,
-                      "pct_cuda_time": 0.2850324247787123,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.704,
-                          "pct_cuda_time": 0.2850324247787123,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 99.733,
-                      "cuda_time_us": 3.776,
-                      "pct_cuda_time": 0.051984275307400386,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.776,
-                          "pct_cuda_time": 0.051984275307400386,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 154.962,
-                      "cuda_time_us": 29.822999999999997,
-                      "pct_cuda_time": 0.4105738989652017,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.272,
-                          "pct_cuda_time": 0.031278674125639214,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.519,
-                          "pct_cuda_time": 0.3237865918842028,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.528,
-                          "pct_cuda_time": 0.034803031773598565,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 25.962,
-                      "cuda_time_us": 18.528,
-                      "pct_cuda_time": 0.25507538477105784,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.528,
-                          "pct_cuda_time": 0.25507538477105784,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.608,
-                  "cuda_time_us": 3.328,
-                  "pct_cuda_time": 0.04581664942347153,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.328,
-                      "pct_cuda_time": 0.04581664942347153,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 96.576,
-                  "cuda_time_us": 131.904,
-                  "pct_cuda_time": 1.8159252781110542,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 32.763,
-                      "cuda_time_us": 79.776,
-                      "pct_cuda_time": 1.0982779520453319,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.776,
-                          "pct_cuda_time": 1.0982779520453319,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 19.99,
-                      "cuda_time_us": 9.088,
-                      "pct_cuda_time": 0.12511469650255685,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 9.088,
-                          "pct_cuda_time": 0.12511469650255685,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 29.77,
-                      "cuda_time_us": 43.04,
-                      "pct_cuda_time": 0.5925326295631654,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.04,
-                          "pct_cuda_time": 0.5925326295631654,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 483.664,
-              "cuda_time_us": 212.127,
-              "pct_cuda_time": 2.920357089018253,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.093,
-                  "cuda_time_us": 3.52,
-                  "pct_cuda_time": 0.04845991765944104,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.52,
-                      "pct_cuda_time": 0.04845991765944104,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 342.872,
-                  "cuda_time_us": 72.512,
-                  "pct_cuda_time": 0.9982743037844855,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 27.648,
-                      "cuda_time_us": 20.384,
-                      "pct_cuda_time": 0.2806269777187631,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.384,
-                          "pct_cuda_time": 0.2806269777187631,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 95.109,
-                      "cuda_time_us": 3.584,
-                      "pct_cuda_time": 0.049341007071430874,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.584,
-                          "pct_cuda_time": 0.049341007071430874,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 158.672,
-                      "cuda_time_us": 30.144,
-                      "pct_cuda_time": 0.4149931130472132,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.304,
-                          "pct_cuda_time": 0.03171921883163414,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.776,
-                          "pct_cuda_time": 0.32732471655422446,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.56,
-                          "pct_cuda_time": 0.03524357647959349,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 26.283,
-                      "cuda_time_us": 18.4,
-                      "pct_cuda_time": 0.2533132059470782,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.4,
-                          "pct_cuda_time": 0.2533132059470782,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.167,
-                  "cuda_time_us": 3.488,
-                  "pct_cuda_time": 0.048019372953446125,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.488,
-                      "pct_cuda_time": 0.048019372953446125,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 96.522,
-                  "cuda_time_us": 132.607,
-                  "pct_cuda_time": 1.8256034946208803,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.51,
-                      "cuda_time_us": 80.639,
-                      "pct_cuda_time": 1.1101588920851324,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 80.639,
-                          "pct_cuda_time": 1.1101588920851324,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.741,
-                      "cuda_time_us": 8.64,
-                      "pct_cuda_time": 0.11894707061862803,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.64,
-                          "pct_cuda_time": 0.11894707061862803,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 30.238,
-                      "cuda_time_us": 43.328,
-                      "pct_cuda_time": 0.5964975319171197,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.328,
-                          "pct_cuda_time": 0.5964975319171197,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 520.5,
-              "cuda_time_us": 211.358,
-              "pct_cuda_time": 2.9097702490523125,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.423,
-                  "cuda_time_us": 3.552,
-                  "pct_cuda_time": 0.048900462365435965,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.552,
-                      "pct_cuda_time": 0.048900462365435965,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 378.082,
-                  "cuda_time_us": 72.92699999999999,
-                  "pct_cuda_time": 1.003987617940357,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 27.63,
-                      "cuda_time_us": 20.608,
-                      "pct_cuda_time": 0.2837107906607276,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.608,
-                          "pct_cuda_time": 0.2837107906607276,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 101.265,
-                      "cuda_time_us": 3.776,
-                      "pct_cuda_time": 0.051984275307400386,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.776,
-                          "pct_cuda_time": 0.051984275307400386,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 170.257,
-                      "cuda_time_us": 29.823,
-                      "pct_cuda_time": 0.4105738989652018,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.4,
-                          "pct_cuda_time": 0.033040852949618886,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.393,
-                          "pct_cuda_time": 0.3220519471043478,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.527,
-                          "pct_cuda_time": 0.03478926475153623,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.503,
-                          "pct_cuda_time": 0.02069183415969883,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 49.754,
-                      "cuda_time_us": 18.72,
-                      "pct_cuda_time": 0.25771865300702734,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.72,
-                          "pct_cuda_time": 0.25771865300702734,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.245,
-                  "cuda_time_us": 3.328,
-                  "pct_cuda_time": 0.04581664942347153,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.328,
-                      "pct_cuda_time": 0.04581664942347153,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 97.28,
-                  "cuda_time_us": 131.551,
-                  "pct_cuda_time": 1.8110655193230476,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 36.124,
-                      "cuda_time_us": 79.968,
-                      "pct_cuda_time": 1.1009212202813015,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.968,
-                          "pct_cuda_time": 1.1009212202813015,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 20.274,
-                      "cuda_time_us": 8.704,
-                      "pct_cuda_time": 0.11982816003061784,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.704,
-                          "pct_cuda_time": 0.11982816003061784,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 29.735,
-                      "cuda_time_us": 42.879,
-                      "pct_cuda_time": 0.5903161390111284,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 42.879,
-                          "pct_cuda_time": 0.5903161390111284,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 514.753,
-              "cuda_time_us": 212.28699999999998,
-              "pct_cuda_time": 2.922559812548227,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 14.005,
-                  "cuda_time_us": 3.616,
-                  "pct_cuda_time": 0.049781551777425805,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.616,
-                      "pct_cuda_time": 0.049781551777425805,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 363.538,
-                  "cuda_time_us": 73.27799999999999,
-                  "pct_cuda_time": 1.0088198426842387,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 34.737,
-                      "cuda_time_us": 21.28,
-                      "pct_cuda_time": 0.2929622294866209,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 21.28,
-                          "pct_cuda_time": 0.2929622294866209,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 109.275,
-                      "cuda_time_us": 3.616,
-                      "pct_cuda_time": 0.049781551777425805,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.616,
-                          "pct_cuda_time": 0.049781551777425805,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 161.711,
-                      "cuda_time_us": 30.046999999999997,
-                      "pct_cuda_time": 0.4136577119071661,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.464,
-                          "pct_cuda_time": 0.033921942361608726,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.519,
-                          "pct_cuda_time": 0.3237865918842028,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.56,
-                          "pct_cuda_time": 0.03524357647959349,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.504,
-                          "pct_cuda_time": 0.020705601181761173,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 28.658,
-                      "cuda_time_us": 18.335,
-                      "pct_cuda_time": 0.252418349513026,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.335,
-                          "pct_cuda_time": 0.252418349513026,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 18.325,
-                  "cuda_time_us": 3.393,
-                  "pct_cuda_time": 0.046711505857523705,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.393,
-                      "pct_cuda_time": 0.046711505857523705,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 104.35,
-                  "cuda_time_us": 132.0,
-                  "pct_cuda_time": 1.817246912229039,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 35.599,
-                      "cuda_time_us": 79.904,
-                      "pct_cuda_time": 1.1000401308693115,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 79.904,
-                          "pct_cuda_time": 1.1000401308693115,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.917,
-                      "cuda_time_us": 8.928,
-                      "pct_cuda_time": 0.12291197297258229,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.928,
-                          "pct_cuda_time": 0.12291197297258229,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 35.428,
-                      "cuda_time_us": 43.168,
-                      "pct_cuda_time": 0.5942948083871451,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 43.168,
-                          "pct_cuda_time": 0.5942948083871451,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "LlamaDecoderLayer",
-              "cpu_time_us": 525.645,
-              "cuda_time_us": 211.199,
-              "pct_cuda_time": 2.9075812925444002,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 15.532,
-                  "cuda_time_us": 3.488,
-                  "pct_cuda_time": 0.048019372953446125,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.488,
-                      "pct_cuda_time": 0.048019372953446125,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaAttention",
-                  "cpu_time_us": 376.326,
-                  "cuda_time_us": 72.607,
-                  "pct_cuda_time": 0.9995821708804078,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "QKVParallelLinear(weight=bfloat16[6144, 4096])",
-                      "cpu_time_us": 30.327,
-                      "cuda_time_us": 20.703,
-                      "pct_cuda_time": 0.28501865775665,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 20.703,
-                          "pct_cuda_time": 0.28501865775665,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 6144]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 6144]) <- linear(bfloat16[1, 4096], bfloat16[6144, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Llama3RotaryEmbedding",
-                      "cpu_time_us": 111.715,
-                      "cuda_time_us": 3.776,
-                      "pct_cuda_time": 0.051984275307400386,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::rotary_embedding_kernel<c10::BFloat16, true>(long const*, c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, int, long, long, int, int, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 3.776,
-                          "pct_cuda_time": 0.051984275307400386,
-                          "trace": "_C::rotary_embedding(int64[1], bfloat16[1, 4096], bfloat16[1, 1024], 128, bfloat16[131072, 128], True)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "Attention",
-                      "cpu_time_us": 173.146,
-                      "cuda_time_us": 30.016,
-                      "pct_cuda_time": 0.4132309342232336,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(__nv_bfloat16 const*, __nv_bfloat16 const*, __nv_bfloat16*, __nv_bfloat16*, long const*, int, int, int, int, int, int, float const*, float const*)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.336,
-                          "pct_cuda_time": 0.03215976353762905,
-                          "trace": "_C_cache_ops::reshape_and_cache_flash(bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], int64[1], None, float32[], float32[]) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > > >(flash::enable_sm90_or_later<flash::FlashAttnFwdSm90<flash::CollectiveMainloopFwdSm90<2, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cutlass::bfloat16_t, float, cutlass::arch::Sm90, true, false, false, true, true, false, true, true, true, true, false>, flash::CollectiveEpilogueFwd<cute::tuple<cute::C<128>, cute::C<128>, cute::C<128> >, cute::tuple<cute::C<1>, cute::C<1>, cute::C<1> >, float, cutlass::arch::Sm90, 256, true, true, false>, flash::VarlenDynamicPersistentTileScheduler<128, 256, 128, true, true, true> > >::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 23.648,
-                          "pct_cuda_time": 0.32556253773024485,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void cutlass::device_kernel<flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80> >(flash::FlashAttnFwdCombine<cute::tuple<cute::C<8>, cute::C<128> >, 5, 256, 1, false, false, cutlass::bfloat16_t, float, cutlass::arch::Sm80>::Params)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 2.527,
-                          "pct_cuda_time": 0.03478926475153623,
-                          "trace": "_vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      },
-                      {
-                        "entry": {
-                          "name": "void at::native::vectorized_elementwise_kernel<4, at::native::FillFunctor<int>, at::detail::Array<char*, 1> >(int, at::native::FillFunctor<int>, at::detail::Array<char*, 1>)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 1.505,
-                          "pct_cuda_time": 0.020719368203823512,
-                          "trace": "fill_(int32[1], 0) <- zero_(int32[1]) <- zeros(None, 3, 0, None, None) <- _vllm_fa3_C::fwd(bfloat16[1, 1, 32, 128], bfloat16[28102, 16, 8, 128], bfloat16[28102, 16, 8, 128], None, None, bfloat16[1, 1, 32, 128], None, None, None, None, int32[1], None, None, int32[1, 257], None, None, None, None, None, None, None, 0.08838834764831845, True, -1, -1, 0, 0.0, True, 0, None, 0) <- vllm::unified_attention_with_output(bfloat16[1, 32, 128], bfloat16[1, 8, 128], bfloat16[1, 8, 128], bfloat16[1, 32, 128], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 4096])",
-                      "cpu_time_us": 27.844,
-                      "cuda_time_us": 18.112,
-                      "pct_cuda_time": 0.24934830359312388,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void gemv2T_kernel_val<int, int, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, float, 128, 16, 4, 4, false, false, cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float> >(cublasGemvParamsEx<int, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16 const>, cublasGemvTensorStridedBatched<__nv_bfloat16>, float>, float, float)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 18.112,
-                          "pct_cuda_time": 0.24934830359312388,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 4096]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 4096]) <- linear(bfloat16[1, 4096], bfloat16[4096, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "RMSNorm(weight=bfloat16[4096])",
-                  "cpu_time_us": 16.427,
-                  "cuda_time_us": 3.552,
-                  "pct_cuda_time": 0.048900462365435965,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                      "cpu_time_us": 0,
-                      "cuda_time_us": 3.552,
-                      "pct_cuda_time": 0.048900462365435965,
-                      "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                    },
-                    "children": []
-                  }
-                ]
-              },
-              {
-                "entry": {
-                  "name": "LlamaMLP",
-                  "cpu_time_us": 103.171,
-                  "cuda_time_us": 131.55200000000002,
-                  "pct_cuda_time": 1.8110792863451106,
-                  "trace": ""
-                },
-                "children": [
-                  {
-                    "entry": {
-                      "name": "MergedColumnParallelLinear(weight=bfloat16[28672, 4096])",
-                      "cpu_time_us": 34.067,
-                      "cuda_time_us": 78.816,
-                      "pct_cuda_time": 1.0850616108654845,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 78.816,
-                          "pct_cuda_time": 1.0850616108654845,
-                          "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 28672]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 28672]) <- linear(bfloat16[1, 4096], bfloat16[28672, 4096], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "SiluAndMul",
-                      "cpu_time_us": 21.306,
-                      "cuda_time_us": 8.736,
-                      "pct_cuda_time": 0.12026870473661277,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "void vllm::act_and_mul_kernel<c10::BFloat16, &(c10::BFloat16 vllm::silu_kernel<c10::BFloat16>(c10::BFloat16 const&)), true>(c10::BFloat16*, c10::BFloat16 const*, int)",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 8.736,
-                          "pct_cuda_time": 0.12026870473661277,
-                          "trace": "_C::silu_and_mul(bfloat16[1, 14336], bfloat16[1, 28672])"
-                        },
-                        "children": []
-                      }
-                    ]
-                  },
-                  {
-                    "entry": {
-                      "name": "RowParallelLinear(weight=bfloat16[4096, 14336])",
-                      "cpu_time_us": 36.455,
-                      "cuda_time_us": 44.0,
-                      "pct_cuda_time": 0.605748970743013,
-                      "trace": ""
-                    },
-                    "children": [
-                      {
-                        "entry": {
-                          "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x64x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-                          "cpu_time_us": 0,
-                          "cuda_time_us": 44.0,
-                          "pct_cuda_time": 0.605748970743013,
-                          "trace": "mm(bfloat16[1, 14336], bfloat16[14336, 4096]) <- matmul(bfloat16[1, 14336], bfloat16[14336, 4096]) <- linear(bfloat16[1, 14336], bfloat16[4096, 14336], None)"
-                        },
-                        "children": []
-                      }
-                    ]
-                  }
-                ]
-              }
-            ]
-          },
-          {
-            "entry": {
-              "name": "RMSNorm(weight=bfloat16[4096])",
-              "cpu_time_us": 15.235,
-              "cuda_time_us": 3.456,
-              "pct_cuda_time": 0.0475788282474512,
-              "trace": ""
-            },
-            "children": [
-              {
-                "entry": {
-                  "name": "std::enable_if<(((8)>(0)))&&vllm::_typeConvert<c10::BFloat16>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, 8>(c10::BFloat16*, c10::BFloat16*, c10::BFloat16 const*, float, int, int)",
-                  "cpu_time_us": 0,
-                  "cuda_time_us": 3.456,
-                  "pct_cuda_time": 0.0475788282474512,
-                  "trace": "_C::fused_add_rms_norm(bfloat16[1, 4096], bfloat16[1, 4096], bfloat16[4096], 1e-05)"
-                },
-                "children": []
-              }
-            ]
-          }
-        ]
-      },
-      {
-        "entry": {
-          "name": "LogitsProcessor",
-          "cpu_time_us": 94.129,
-          "cuda_time_us": 347.518,
-          "pct_cuda_time": 4.784287973060691,
-          "trace": ""
-        },
-        "children": [
-          {
-            "entry": {
-              "name": "void at::native::(anonymous namespace)::indexSelectSmallIndex<c10::BFloat16, long, unsigned int, 2, 2, -2>(at::cuda::detail::TensorInfo<c10::BFloat16, unsigned int>, at::cuda::detail::TensorInfo<c10::BFloat16 const, unsigned int>, at::cuda::detail::TensorInfo<long const, unsigned int>, int, int, unsigned int, long)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.624,
-              "pct_cuda_time": 0.03612466589158332,
-              "trace": "index_select(bfloat16[1, 4096], 0, int64[1])"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memset (Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 0.735,
-              "pct_cuda_time": 0.010118761215820785,
-              "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 128256]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 128256]) <- linear(bfloat16[1, 4096], bfloat16[128256, 4096], None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "sm90_xmma_gemm_bf16bf16_bf16f32_f32_tn_n_tilesize64x128x64_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
-              "cpu_time_us": 0,
-              "cuda_time_us": 344.159,
-              "pct_cuda_time": 4.7380445459532865,
-              "trace": "mm(bfloat16[1, 4096], bfloat16[4096, 128256]) <- matmul(bfloat16[1, 4096], bfloat16[4096, 128256]) <- linear(bfloat16[1, 4096], bfloat16[128256, 4096], None)"
-            },
-            "children": []
-          }
-        ]
-      },
-      {
-        "entry": {
-          "name": "Sampler",
-          "cpu_time_us": 684.941,
-          "cuda_time_us": 124.28700000000002,
-          "pct_cuda_time": 1.7110618710622016,
-          "trace": ""
-        },
-        "children": [
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.815,
-              "pct_cuda_time": 0.03875416710549049,
-              "trace": "copy_(bfloat16[1], bfloat16[1], True) <- _to_copy(bfloat16[1], 15, 0, None, None, True, None) <- to(bfloat16[1], 15, 0, None, None, True, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.208,
-              "pct_cuda_time": 0.03039758471364938,
-              "trace": "copy_(bfloat16[1], bfloat16[1], True) <- _to_copy(bfloat16[1], 15, 0, None, None, True, None) <- to(bfloat16[1], 15, 0, None, None, True, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.208,
-              "pct_cuda_time": 0.03039758471364938,
-              "trace": "copy_(int32[1], int32[1], True) <- _to_copy(int32[1], 3, 0, None, None, True, None) <- to(int32[1], 3, 0, None, None, True, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.208,
-              "pct_cuda_time": 0.03039758471364938,
-              "trace": "copy_(bfloat16[1], bfloat16[1], True) <- _to_copy(bfloat16[1], 15, 0, None, None, True, None) <- to(bfloat16[1], 15, 0, None, None, True, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.24,
-              "pct_cuda_time": 0.0308381294196443,
-              "trace": "copy_(bfloat16[1], bfloat16[1], True) <- _to_copy(bfloat16[1], 15, 0, None, None, True, None) <- to(bfloat16[1], 15, 0, None, None, True, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.208,
-              "pct_cuda_time": 0.03039758471364938,
-              "trace": "copy_(bfloat16[1], bfloat16[1], True) <- _to_copy(bfloat16[1], 15, 0, None, None, True, None) <- to(bfloat16[1], 15, 0, None, None, True, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy HtoD (Pinned -> Device)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.144,
-              "pct_cuda_time": 0.02951649530165954,
-              "trace": "copy_(bfloat16[1], bfloat16[1], True) <- _to_copy(bfloat16[1], 15, 0, None, None, True, None) <- to(bfloat16[1], 15, 0, None, None, True, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#7}::operator()() const::{lambda(float)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1> >(int, at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#7}::operator()() const::{lambda(float)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1>)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 4.192,
-              "pct_cuda_time": 0.057711356485334334,
-              "trace": "copy_(float32[1, 128256], bfloat16[1, 128256], False) <- _to_copy(bfloat16[1, 128256], 6, None, None, None, False, None) <- to(bfloat16[1, 128256], 6, False, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::elementwise_kernel<128, 4, at::native::gpu_kernel_impl<at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > >(at::TensorIteratorBase&, at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > const&)::{lambda(int)#1}>(int, at::native::gpu_kernel_impl<at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > >(at::TensorIteratorBase&, at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float> > const&)::{lambda(int)#1})",
-              "cpu_time_us": 0,
-              "cuda_time_us": 4.512,
-              "pct_cuda_time": 0.062116803545283504,
-              "trace": "div_(float32[1, 128256], bfloat16[1, 1])"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::(anonymous namespace)::cunn_SoftMaxForward<4, float, float, float, at::native::(anonymous namespace)::SoftMaxForwardEpilogue>(float*, float const*, int)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 34.08,
-              "pct_cuda_time": 0.46918011188458825,
-              "trace": "_softmax(float32[1, 128256], -1, False) <- softmax(float32[1, 128256], -1, 6)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::(anonymous namespace)::cunn_SoftMaxForward<4, float, float, float, at::native::(anonymous namespace)::LogSoftMaxForwardEpilogue>(float*, float const*, int)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 27.584,
-              "pct_cuda_time": 0.3797495365676198,
-              "trace": "_log_softmax(float32[1, 128256], -1, False) <- log_softmax(float32[1, 128256], -1, 6)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#4}::operator()() const::{lambda(long)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1> >(int, at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#4}::operator()() const::{lambda(long)#1}, at::detail::Array<char*, 2>, TrivialOffsetCalculator<1, unsigned int>, TrivialOffsetCalculator<1, unsigned int>, at::native::memory::LoadWithCast<1>, at::native::memory::StoreWithCast<1>)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 1.888,
-              "pct_cuda_time": 0.025992137653700193,
-              "trace": "copy_(int64[1], int32[1], False) <- _to_copy(int32[1], 4, None, None, None, False, None) <- to(int32[1], 4, False, False, None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::index_elementwise_kernel<128, 4, at::native::gpu_index_kernel<at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1}>(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>, at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1} const&)::{lambda(int)#1}>(long, at::native::gpu_index_kernel<at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1}>(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>, at::native::index_kernel_impl<at::native::OpaqueType<4> >(at::TensorIteratorBase&, c10::ArrayRef<long>, c10::ArrayRef<long>)::{lambda(char*, char const*, long)#1} const&)::{lambda(int)#1})",
-              "cpu_time_us": 0,
-              "cuda_time_us": 4.64,
-              "pct_cuda_time": 0.06387898236926319,
-              "trace": "index(float32[1, 128256], None)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "void at::native::reduce_kernel<512, 1, at::native::ReduceOp<float, at::native::ArgMaxOps<float>, unsigned int, long, 4> >(at::native::ReduceOp<float, at::native::ArgMaxOps<float>, unsigned int, long, 4>)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 28.576,
-              "pct_cuda_time": 0.3934064224534623,
-              "trace": "argmax(float32[1, 128256], -1, False)"
-            },
-            "children": []
-          },
-          {
-            "entry": {
-              "name": "Memcpy DtoH (Device -> Pageable)",
-              "cpu_time_us": 0,
-              "cuda_time_us": 2.784,
-              "pct_cuda_time": 0.03832738942155792,
-              "trace": "copy_(int64[1], int64[1], False) <- _to_copy(int64[1], 4, 0, None, None, False, None) <- to(int64[1], 4, 0, None, None, False, False, None)"
-            },
-            "children": []
-          }
-        ]
-      }
-    ]
-  }
-}
\ No newline at end of file