WARNING: CPU IP/backtrace sampling not supported, disabling.
Try the 'nsys status --environment' command to learn more.

WARNING: CPU context switch tracing not supported, disabling.
Try the 'nsys status --environment' command to learn more.

INFO 08-13 19:21:37 [__init__.py:235] Automatically detected platform cuda.
CUDA_VISIBLE_DEVICES = 3
--- vLLM V1 基准测试（含 NVTX 标记）---
模型: Qwen/Qwen2-1.5B
批量大小: [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024]
场景: ['prefill1_decode512']
------------------------------------------------------------
加载分词器/模型中...
INFO 08-13 19:21:46 [config.py:1604] Using max model len 4096
INFO 08-13 19:21:47 [config.py:2434] Chunked prefill is enabled with max_num_batched_tokens=8192.
INFO 08-13 19:21:52 [__init__.py:235] Automatically detected platform cuda.
INFO 08-13 19:21:54 [core.py:572] Waiting for init message from front-end.
INFO 08-13 19:21:54 [core.py:71] Initializing a V1 LLM engine (v0.10.0) with config: model='Qwen/Qwen2-1.5B', speculative_config=None, tokenizer='Qwen/Qwen2-1.5B', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, override_neuron_config={}, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=4096, download_dir=None, load_format=LoadFormat.AUTO, tensor_parallel_size=1, pipeline_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto,  device_config=cuda, decoding_config=DecodingConfig(backend='auto', disable_fallback=False, disable_any_whitespace=False, disable_additional_properties=False, reasoning_backend=''), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None), seed=0, served_model_name=Qwen/Qwen2-1.5B, num_scheduler_steps=1, multi_step_stream_outputs=True, enable_prefix_caching=True, chunked_prefill_enabled=True, use_async_output_proc=True, pooler_config=None, compilation_config={"level":3,"debug_dump_path":"","cache_dir":"","backend":"","custom_ops":[],"splitting_ops":["vllm.unified_attention","vllm.unified_attention_with_output","vllm.mamba_mixer2"],"use_inductor":true,"compile_sizes":[],"inductor_compile_config":{"enable_auto_functionalized_v2":false},"inductor_passes":{},"use_cudagraph":true,"cudagraph_num_of_warmups":1,"cudagraph_capture_sizes":[512,504,496,488,480,472,464,456,448,440,432,424,416,408,400,392,384,376,368,360,352,344,336,328,320,312,304,296,288,280,272,264,256,248,240,232,224,216,208,200,192,184,176,168,160,152,144,136,128,120,112,104,96,88,80,72,64,56,48,40,32,24,16,8,4,2,1],"cudagraph_copy_inputs":false,"full_cuda_graph":false,"max_capture_size":512,"local_cache_dir":null}
INFO 08-13 19:21:56 [parallel_state.py:1102] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, TP rank 0, EP rank 0
WARNING 08-13 19:21:56 [topk_topp_sampler.py:59] FlashInfer is not available. Falling back to the PyTorch-native implementation of top-p & top-k sampling. For the best performance, please install FlashInfer.
INFO 08-13 19:21:56 [gpu_model_runner.py:1843] Starting to load model Qwen/Qwen2-1.5B...
INFO 08-13 19:21:56 [gpu_model_runner.py:1875] Loading model from scratch...
INFO 08-13 19:21:56 [cuda.py:290] Using Flash Attention backend on V1 engine.
INFO 08-13 19:21:57 [weight_utils.py:296] Using model weights format ['*.safetensors']
INFO 08-13 19:21:57 [weight_utils.py:349] No model.safetensors.index.json found in remote.

Loading safetensors checkpoint shards:   0% Completed | 0/1 [00:00<?, ?it/s]

Loading safetensors checkpoint shards: 100% Completed | 1/1 [00:00<00:00,  1.81it/s]

Loading safetensors checkpoint shards: 100% Completed | 1/1 [00:00<00:00,  1.81it/s]

INFO 08-13 19:21:58 [default_loader.py:262] Loading weights took 0.63 seconds
INFO 08-13 19:21:58 [gpu_model_runner.py:1892] Model loading took 2.9105 GiB and 1.878581 seconds
INFO 08-13 19:22:04 [backends.py:530] Using cache directory: /home/cy/.cache/vllm/torch_compile_cache/40b61c71e9/rank_0_0/backbone for vLLM's torch.compile
INFO 08-13 19:22:04 [backends.py:541] Dynamo bytecode transform time: 5.72 s
INFO 08-13 19:22:09 [backends.py:161] Directly load the compiled graph(s) for dynamic shape from the cache, took 4.036 s
INFO 08-13 19:22:10 [monitor.py:34] torch.compile takes 5.72 s in total
INFO 08-13 19:22:11 [gpu_worker.py:255] Available KV cache memory: 12.81 GiB
INFO 08-13 19:22:11 [kv_cache_utils.py:833] GPU KV cache size: 479,536 tokens
INFO 08-13 19:22:11 [kv_cache_utils.py:837] Maximum concurrency for 4,096 tokens per request: 117.07x

Capturing CUDA graph shapes:   0%|          | 0/67 [00:00<?, ?it/s]
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Capturing CUDA graph shapes:  66%|██████▌   | 44/67 [00:01<00:00, 33.67it/s]
Capturing CUDA graph shapes:  72%|███████▏  | 48/67 [00:01<00:00, 34.02it/s]
Capturing CUDA graph shapes:  78%|███████▊  | 52/67 [00:01<00:00, 33.79it/s]
Capturing CUDA graph shapes:  84%|████████▎ | 56/67 [00:01<00:00, 33.45it/s]
Capturing CUDA graph shapes:  90%|████████▉ | 60/67 [00:01<00:00, 33.53it/s]
Capturing CUDA graph shapes:  96%|█████████▌| 64/67 [00:01<00:00, 32.97it/s]
Capturing CUDA graph shapes: 100%|██████████| 67/67 [00:01<00:00, 33.62it/s]
INFO 08-13 19:22:13 [gpu_model_runner.py:2485] Graph capturing finished in 2 secs, took 0.49 GiB
INFO 08-13 19:22:13 [core.py:193] init engine (profile, create kv cache, warmup model) took 14.62 seconds
模型加载完成。

===== 场景：prefill1_decode512 | prefill=1, decode=512 =====

--- 批量大小 bs=1 ---

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Adding requests: 100%|██████████| 1/1 [00:00<00:00, 767.20it/s]

Processed prompts:   0%|          | 0/1 [00:00<?, ?it/s, est. speed input: 0.00 toks/s, output: 0.00 toks/s]
Processed prompts: 100%|██████████| 1/1 [00:03<00:00,  3.31s/it, est. speed input: 0.30 toks/s, output: 154.57 toks/s]
Processed prompts: 100%|██████████| 1/1 [00:03<00:00,  3.31s/it, est. speed input: 0.30 toks/s, output: 154.57 toks/s]
Processed prompts: 100%|██████████| 1/1 [00:03<00:00,  3.31s/it, est. speed input: 0.30 toks/s, output: 154.57 toks/s]
执行时间: 3.3194 s
实际平均输入 tokens: 1.00（目标 1）
生成总 tokens: 512
吞吐(生成tokens/秒): 154.24
TTFT (V1 metrics): 0.0190 s
解码吞吐 (V1 metrics): 155.07 tok/s

--- 批量大小 bs=2 ---

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Adding requests: 100%|██████████| 2/2 [00:00<00:00, 1154.03it/s]

Processed prompts:   0%|          | 0/2 [00:00<?, ?it/s, est. speed input: 0.00 toks/s, output: 0.00 toks/s]
Processed prompts:  50%|█████     | 1/2 [00:03<00:03,  3.64s/it, est. speed input: 0.27 toks/s, output: 140.74 toks/s]
Processed prompts: 100%|██████████| 2/2 [00:03<00:00,  3.64s/it, est. speed input: 0.55 toks/s, output: 280.95 toks/s]
Processed prompts: 100%|██████████| 2/2 [00:03<00:00,  1.82s/it, est. speed input: 0.55 toks/s, output: 280.95 toks/s]
执行时间: 3.6484 s
实际平均输入 tokens: 1.00（目标 1）
生成总 tokens: 1024
吞吐(生成tokens/秒): 280.67
TTFT (V1 metrics): 0.0120 s
解码吞吐 (V1 metrics): 140.73 tok/s

--- 批量大小 bs=4 ---

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Adding requests: 100%|██████████| 4/4 [00:00<00:00, 1830.57it/s]

Processed prompts:   0%|          | 0/4 [00:00<?, ?it/s, est. speed input: 0.00 toks/s, output: 0.00 toks/s]
Processed prompts:  25%|██▌       | 1/4 [00:03<00:10,  3.62s/it, est. speed input: 0.28 toks/s, output: 141.26 toks/s]
Processed prompts: 100%|██████████| 4/4 [00:03<00:00,  3.62s/it, est. speed input: 1.10 toks/s, output: 563.84 toks/s]
Processed prompts: 100%|██████████| 4/4 [00:03<00:00,  1.10it/s, est. speed input: 1.10 toks/s, output: 563.84 toks/s]
执行时间: 3.6361 s
实际平均输入 tokens: 1.00（目标 1）
生成总 tokens: 2048
吞吐(生成tokens/秒): 563.24
TTFT (V1 metrics): 0.0140 s
解码吞吐 (V1 metrics): 141.25 tok/s

--- 批量大小 bs=8 ---

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Adding requests: 100%|██████████| 8/8 [00:00<00:00, 1658.07it/s]

Processed prompts:   0%|          | 0/8 [00:00<?, ?it/s, est. speed input: 0.00 toks/s, output: 0.00 toks/s]
Processed prompts:  12%|█▎        | 1/8 [00:03<00:25,  3.71s/it, est. speed input: 0.27 toks/s, output: 137.92 toks/s]
Processed prompts: 100%|██████████| 8/8 [00:03<00:00,  3.71s/it, est. speed input: 2.15 toks/s, output: 1101.10 toks/s]
Processed prompts: 100%|██████████| 8/8 [00:03<00:00,  2.15it/s, est. speed input: 2.15 toks/s, output: 1101.10 toks/s]
执行时间: 3.7267 s
实际平均输入 tokens: 1.00（目标 1）
生成总 tokens: 4096
吞吐(生成tokens/秒): 1099.08
TTFT (V1 metrics): 0.0149 s
解码吞吐 (V1 metrics): 137.87 tok/s

--- 批量大小 bs=16 ---

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Adding requests: 100%|██████████| 16/16 [00:00<00:00, 1911.61it/s]

Processed prompts:   0%|          | 0/16 [00:00<?, ?it/s, est. speed input: 0.00 toks/s, output: 0.00 toks/s]
Processed prompts:   6%|▋         | 1/16 [00:03<00:57,  3.81s/it, est. speed input: 0.26 toks/s, output: 134.53 toks/s]
Processed prompts: 100%|██████████| 16/16 [00:03<00:00,  3.81s/it, est. speed input: 4.19 toks/s, output: 2147.16 toks/s]
Processed prompts: 100%|██████████| 16/16 [00:03<00:00,  4.19it/s, est. speed input: 4.19 toks/s, output: 2147.16 toks/s]
执行时间: 3.8260 s
实际平均输入 tokens: 1.00（目标 1）
生成总 tokens: 8192
吞吐(生成tokens/秒): 2141.13
TTFT (V1 metrics): 0.0136 s
解码吞吐 (V1 metrics): 134.33 tok/s

--- 批量大小 bs=32 ---

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Adding requests: 100%|██████████| 32/32 [00:00<00:00, 1946.85it/s]

Processed prompts:   0%|          | 0/32 [00:00<?, ?it/s, est. speed input: 0.00 toks/s, output: 0.00 toks/s]
Processed prompts:   3%|▎         | 1/32 [00:03<02:02,  3.96s/it, est. speed input: 0.25 toks/s, output: 129.29 toks/s]
Processed prompts: 100%|██████████| 32/32 [00:03<00:00,  3.96s/it, est. speed input: 8.04 toks/s, output: 4118.30 toks/s]
Processed prompts: 100%|██████████| 32/32 [00:03<00:00,  8.04it/s, est. speed input: 8.04 toks/s, output: 4118.30 toks/s]
执行时间: 3.9972 s
实际平均输入 tokens: 1.00（目标 1）
生成总 tokens: 16384
吞吐(生成tokens/秒): 4098.85
TTFT (V1 metrics): 0.0164 s
解码吞吐 (V1 metrics): 128.92 tok/s

--- 批量大小 bs=64 ---

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Adding requests: 100%|██████████| 64/64 [00:00<00:00, 2745.78it/s]

Processed prompts:   0%|          | 0/64 [00:00<?, ?it/s, est. speed input: 0.00 toks/s, output: 0.00 toks/s]
Processed prompts:   2%|▏         | 1/64 [00:04<04:25,  4.22s/it, est. speed input: 0.24 toks/s, output: 121.28 toks/s]
Processed prompts: 100%|██████████| 64/64 [00:04<00:00,  4.22s/it, est. speed input: 15.07 toks/s, output: 7714.52 toks/s]
Processed prompts: 100%|██████████| 64/64 [00:04<00:00, 15.07it/s, est. speed input: 15.07 toks/s, output: 7714.52 toks/s]
执行时间: 4.2731 s
实际平均输入 tokens: 1.00（目标 1）
生成总 tokens: 32768
吞吐(生成tokens/秒): 7668.51
TTFT (V1 metrics): 0.0198 s
解码吞吐 (V1 metrics): 120.83 tok/s

--- 批量大小 bs=128 ---

Adding requests:   0%|          | 0/128 [00:00<?, ?it/s]
Adding requests: 100%|██████████| 128/128 [00:00<00:00, 2211.91it/s]

Processed prompts:   0%|          | 0/128 [00:00<?, ?it/s, est. speed input: 0.00 toks/s, output: 0.00 toks/s]
Processed prompts:   1%|          | 1/128 [00:04<09:58,  4.71s/it, est. speed input: 0.21 toks/s, output: 108.61 toks/s]
Processed prompts: 100%|██████████| 128/128 [00:04<00:00,  4.71s/it, est. speed input: 26.77 toks/s, output: 13706.03 toks/s]
Processed prompts: 100%|██████████| 128/128 [00:04<00:00, 26.77it/s, est. speed input: 26.77 toks/s, output: 13706.03 toks/s]
执行时间: 4.8421 s
实际平均输入 tokens: 1.00（目标 1）
生成总 tokens: 65536
吞吐(生成tokens/秒): 13534.75
TTFT (V1 metrics): 0.0316 s
解码吞吐 (V1 metrics): 107.35 tok/s

--- 批量大小 bs=256 ---

Adding requests:   0%|          | 0/256 [00:00<?, ?it/s]
Adding requests: 100%|██████████| 256/256 [00:00<00:00, 3033.50it/s]

Processed prompts:   0%|          | 0/256 [00:00<?, ?it/s, est. speed input: 0.00 toks/s, output: 0.00 toks/s]
Processed prompts:   0%|          | 1/256 [00:07<30:48,  7.25s/it, est. speed input: 0.14 toks/s, output: 70.63 toks/s]
Processed prompts:  91%|█████████ | 232/256 [00:07<00:00, 44.78it/s, est. speed input: 31.57 toks/s, output: 16162.98 toks/s]
Processed prompts: 100%|██████████| 256/256 [00:07<00:00, 44.78it/s, est. speed input: 34.82 toks/s, output: 17826.08 toks/s]
Processed prompts: 100%|██████████| 256/256 [00:07<00:00, 34.81it/s, est. speed input: 34.82 toks/s, output: 17826.08 toks/s]
执行时间: 7.4408 s
实际平均输入 tokens: 1.00（目标 1）
生成总 tokens: 131072
吞吐(生成tokens/秒): 17615.41
TTFT (V1 metrics): 0.0433 s
解码吞吐 (V1 metrics): 69.70 tok/s

--- 批量大小 bs=512 ---

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Adding requests:  28%|██▊       | 142/512 [00:00<00:00, 419.62it/s]
Adding requests:  77%|███████▋  | 394/512 [00:00<00:00, 1042.72it/s]
Adding requests: 100%|██████████| 512/512 [00:00<00:00, 1097.09it/s]

Processed prompts:   0%|          | 0/512 [00:00<?, ?it/s, est. speed input: 0.00 toks/s, output: 0.00 toks/s]
Processed prompts:   0%|          | 1/512 [00:11<1:35:54, 11.26s/it, est. speed input: 0.09 toks/s, output: 45.47 toks/s]
Processed prompts:  16%|█▌        | 82/512 [00:11<00:42, 10.22it/s, est. speed input: 7.21 toks/s, output: 3691.96 toks/s]
Processed prompts:  30%|███       | 156/512 [00:12<00:17, 20.80it/s, est. speed input: 12.91 toks/s, output: 6610.35 toks/s]
Processed prompts:  63%|██████▎   | 321/512 [00:12<00:03, 56.88it/s, est. speed input: 26.35 toks/s, output: 13489.37 toks/s]
Processed prompts: 100%|██████████| 512/512 [00:12<00:00, 56.88it/s, est. speed input: 41.94 toks/s, output: 21474.03 toks/s]
Processed prompts: 100%|██████████| 512/512 [00:12<00:00, 41.94it/s, est. speed input: 41.94 toks/s, output: 21474.03 toks/s]
执行时间: 12.6794 s
实际平均输入 tokens: 1.00（目标 1）
生成总 tokens: 262144
吞吐(生成tokens/秒): 20674.72
TTFT (V1 metrics): 0.1809 s
解码吞吐 (V1 metrics): 42.38 tok/s

--- 批量大小 bs=1024 ---

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Adding requests:  46%|████▌     | 467/1024 [00:00<00:00, 4667.43it/s]
Adding requests: 100%|██████████| 1024/1024 [00:00<00:00, 5118.73it/s]

Processed prompts:   0%|          | 0/1024 [00:00<?, ?it/s, est. speed input: 0.00 toks/s, output: 0.00 toks/s]
Processed prompts:   0%|          | 1/1024 [00:23<6:45:27, 23.78s/it, est. speed input: 0.04 toks/s, output: 21.53 toks/s]
Processed prompts:   0%|          | 3/1024 [00:24<1:47:55,  6.34s/it, est. speed input: 0.12 toks/s, output: 63.32 toks/s]
Processed prompts:   4%|▍         | 43/1024 [00:24<04:44,  3.45it/s, est. speed input: 1.76 toks/s, output: 902.23 toks/s]
Processed prompts:  14%|█▍        | 141/1024 [00:24<00:59, 14.82it/s, est. speed input: 5.75 toks/s, output: 2946.22 toks/s]
Processed prompts:  41%|████      | 416/1024 [00:24<00:10, 59.55it/s, est. speed input: 16.91 toks/s, output: 8657.05 toks/s]
Processed prompts:  93%|█████████▎| 951/1024 [00:24<00:00, 178.49it/s, est. speed input: 38.43 toks/s, output: 19674.52 toks/s]
Processed prompts: 100%|██████████| 1024/1024 [00:25<00:00, 178.49it/s, est. speed input: 40.84 toks/s, output: 20911.92 toks/s]
Processed prompts: 100%|██████████| 1024/1024 [00:25<00:00, 40.84it/s, est. speed input: 40.84 toks/s, output: 20911.92 toks/s] 
[rank0]:[W813 19:23:32.135663883 ProcessGroupNCCL.cpp:1479] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator())
执行时间: 25.2865 s
实际平均输入 tokens: 1.00（目标 1）
生成总 tokens: 524288
吞吐(生成tokens/秒): 20733.89
TTFT (V1 metrics): 0.1191 s
解码吞吐 (V1 metrics): 20.77 tok/s

完成。提示：在 Nsight Systems 中可通过 NVTX 区间快速定位各场景/批量的调用。
GPU 3: General Metrics for NVIDIA AD10x (any frequency)
Generating '/tmp/nsys-report-bd68.qdstrm'

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[3/8] Executing 'nvtx_sum' stats report

 Time (%)  Total Time (ns)  Instances      Avg (ns)          Med (ns)         Min (ns)        Max (ns)     StdDev (ns)   Style                   Range                 
 --------  ---------------  ---------  ----------------  ----------------  --------------  --------------  -----------  -------  --------------------------------------
     31.5   35,202,819,763          1  35,202,819,763.0  35,202,819,763.0  35,202,819,763  35,202,819,763          0.0  PushPop  :LLM_init                             
     22.6   25,285,906,551          1  25,285,906,551.0  25,285,906,551.0  25,285,906,551  25,285,906,551          0.0  PushPop  :generate [prefill1_decode512] bs=1024
     11.3   12,679,311,252          1  12,679,311,252.0  12,679,311,252.0  12,679,311,252  12,679,311,252          0.0  PushPop  :generate [prefill1_decode512] bs=512 
      6.7    7,440,608,085          1   7,440,608,085.0   7,440,608,085.0   7,440,608,085   7,440,608,085          0.0  PushPop  :generate [prefill1_decode512] bs=256 
      4.3    4,841,914,697          1   4,841,914,697.0   4,841,914,697.0   4,841,914,697   4,841,914,697          0.0  PushPop  :generate [prefill1_decode512] bs=128 
      3.8    4,272,889,441          1   4,272,889,441.0   4,272,889,441.0   4,272,889,441   4,272,889,441          0.0  PushPop  :generate [prefill1_decode512] bs=64  
      3.6    3,997,075,015          1   3,997,075,015.0   3,997,075,015.0   3,997,075,015   3,997,075,015          0.0  PushPop  :generate [prefill1_decode512] bs=32  
      3.4    3,825,710,172          1   3,825,710,172.0   3,825,710,172.0   3,825,710,172   3,825,710,172          0.0  PushPop  :generate [prefill1_decode512] bs=16  
      3.3    3,726,603,655          1   3,726,603,655.0   3,726,603,655.0   3,726,603,655   3,726,603,655          0.0  PushPop  :generate [prefill1_decode512] bs=8   
      3.3    3,648,294,896          1   3,648,294,896.0   3,648,294,896.0   3,648,294,896   3,648,294,896          0.0  PushPop  :generate [prefill1_decode512] bs=2   
      3.2    3,635,960,724          1   3,635,960,724.0   3,635,960,724.0   3,635,960,724   3,635,960,724          0.0  PushPop  :generate [prefill1_decode512] bs=4   
      3.0    3,319,210,677          1   3,319,210,677.0   3,319,210,677.0   3,319,210,677   3,319,210,677          0.0  PushPop  :generate [prefill1_decode512] bs=1   
      0.0           90,630          2          45,315.0          45,315.0          41,468          49,162      5,440.5  PushPop  CCCL:cub::DeviceSegmentedRadixSort    

[4/8] Executing 'osrt_sum' stats report

 Time (%)   Total Time (ns)   Num Calls     Avg (ns)          Med (ns)      Min (ns)      Max (ns)       StdDev (ns)              Name         
 --------  -----------------  ---------  ---------------  ----------------  ---------  --------------  ----------------  ----------------------
     29.7  1,284,023,267,442     49,709     25,830,800.6          28,820.0      1,000  96,534,138,823     969,651,617.8  pthread_cond_timedwait
     24.2  1,045,773,118,476     73,135     14,299,215.4      10,062,843.0      1,010  81,708,518,315     463,992,514.8  epoll_wait            
     23.9  1,031,963,983,489        549  1,879,715,816.9          15,827.0      1,644  96,535,575,076  13,212,126,179.1  pthread_cond_wait     
      8.3    357,289,068,553         57  6,268,229,272.9  10,000,073,611.0     10,419  10,000,146,360   4,730,020,985.8  sem_timedwait         
      8.2    355,562,427,280     39,343      9,037,501.6           1,512.0      1,000  12,219,368,064     127,255,975.8  poll                  
      3.0    131,715,516,186     11,467     11,486,484.4       7,170,376.0     28,456     585,263,318      14,022,810.8  sem_wait              
      2.6    112,179,081,690     41,286      2,717,121.6           2,213.0      1,000  94,667,308,194     468,888,772.5  read                  
      0.0        793,423,700        330      2,404,314.2       1,354,549.5      1,900      18,406,079       2,639,127.9  pthread_rwlock_wrlock 
      0.0        494,035,258    199,029          2,482.2           1,380.0      1,000      72,123,224         161,811.1  munmap                
      0.0        298,099,876      8,608         34,630.6          10,089.5      1,002      29,694,619         390,579.6  ioctl                 
      0.0        220,903,685        369        598,655.0           2,510.0      1,159      22,536,588       3,264,985.3  fopen                 
      0.0        121,576,605         24      5,065,691.9       5,064,718.5  5,053,737       5,087,479           7,589.0  nanosleep             
      0.0        110,429,690     30,645          3,603.5           2,536.0      1,000      19,587,041         111,890.3  open64                
      0.0         88,325,670         79      1,118,046.5           3,103.0      1,011      81,521,546       9,166,201.0  waitpid               
      0.0         76,471,088     18,154          4,212.4           3,660.0      1,000       1,659,563          15,417.3  mmap64                
      0.0         74,586,704         96        776,944.8           3,874.0      1,020      19,635,272       3,727,062.1  open                  
      0.0         72,521,171      8,897          8,151.2           4,707.0      1,022       2,826,985          34,660.7  recv                  
      0.0         71,841,066      8,895          8,076.6           5,429.0      1,571          84,986           7,239.5  send                  
      0.0         69,801,955     41,067          1,699.7           1,627.0      1,000          32,060             794.7  pthread_cond_signal   
      0.0         67,085,379         39      1,720,137.9         470,979.0      3,544      10,373,042       3,340,509.2  pthread_join          
      0.0         56,617,564         10      5,661,756.4          18,705.5      8,315      56,388,994      17,823,747.2  connect               
      0.0         51,207,160     14,809          3,457.8           2,380.0      1,013         139,725           5,733.7  write                 
      0.0         40,211,592      4,773          8,424.8           6,319.0      1,000         661,710          13,119.1  pthread_mutex_lock    
      0.0         16,225,859     10,123          1,602.9           1,387.0      1,000          17,416             730.6  epoll_ctl             
      0.0          9,852,733        147         67,025.4          68,737.0     55,805          95,256           5,155.2  sleep                 
      0.0          7,858,705         22        357,213.9         474,706.5      8,796         678,261         278,233.7  pthread_rwlock_rdlock 
      0.0          7,721,440        131         58,942.3          56,260.0     21,296         195,560          26,034.2  pthread_create        
      0.0          7,224,126        929          7,776.2           3,096.0      1,000          86,864          11,142.9  fgets                 
      0.0          1,723,609        344          5,010.5           4,755.0      1,827          40,649           2,516.1  fopen64               
      0.0          1,708,972         62         27,564.1           2,983.5      1,002         230,421          59,773.0  futex                 
      0.0          1,347,355      1,069          1,260.4           1,023.0      1,000          12,904             880.3  fclose                
      0.0          1,149,466        196          5,864.6           3,579.5      1,105         168,420          13,582.2  mmap                  
      0.0            878,967          1        878,967.0         878,967.0    878,967         878,967               0.0  fork                  
      0.0            364,215         65          5,603.3           5,028.0      1,909          15,104           3,123.9  pipe2                 
      0.0            247,833         41          6,044.7           4,941.0      1,709          17,457           4,172.6  socket                
      0.0            188,362         19          9,913.8           3,097.0      1,045          62,742          16,639.4  bind                  
      0.0            128,433         34          3,777.4           3,261.0      1,187          14,840           2,461.4  pthread_cond_broadcast
      0.0             76,747          7         10,963.9           9,959.0      3,576          31,262           9,493.1  fread                 
      0.0             65,399         41          1,595.1           1,200.0      1,012           5,988           1,063.6  fcntl                 
      0.0             49,079          5          9,815.8           9,542.0      4,750          17,158           4,761.0  accept4               
      0.0             42,725         25          1,709.0           1,806.0      1,011           2,296             397.2  sigaction             
      0.0             40,441         20          2,022.1           2,166.5      1,063           3,618             818.8  dup2                  
      0.0             39,878         15          2,658.5           2,065.0      1,267           7,040           1,459.6  stat                  
      0.0             31,245         12          2,603.8           1,918.0      1,006           5,220           1,771.4  fflush                
      0.0             27,179          5          5,435.8           5,277.0      1,662           9,374           3,035.3  fwrite                
      0.0             21,540          4          5,385.0           5,545.5      4,572           5,877             575.6  lstat                 
      0.0             17,255          4          4,313.8           4,516.5      2,856           5,366           1,051.1  flock                 
      0.0             16,827          9          1,869.7           1,599.0      1,008           3,313             844.3  pread                 
      0.0             15,569         10          1,556.9           1,444.0      1,184           2,260             325.7  listen                
      0.0             13,074          3          4,358.0           4,294.0      4,285           4,495             118.7  fputs_unlocked        
      0.0             12,439          5          2,487.8           2,713.0      1,831           3,023             566.6  mprotect              
      0.0              7,489          4          1,872.3           1,856.5      1,636           2,140             206.8  flockfile             
      0.0              6,919          1          6,919.0           6,919.0      6,919           6,919               0.0  kill                  
      0.0              5,460          2          2,730.0           2,730.0      2,008           3,452           1,021.1  openat64              
      0.0              5,297          3          1,765.7           1,842.0      1,157           2,298             574.3  fstat                 
      0.0              3,627          1          3,627.0           3,627.0      3,627           3,627               0.0  fputs                 

[5/8] Executing 'cuda_api_sum' stats report

 Time (%)  Total Time (ns)  Num Calls   Avg (ns)     Med (ns)    Min (ns)   Max (ns)    StdDev (ns)                     Name                   
 --------  ---------------  ---------  -----------  -----------  --------  -----------  -----------  ------------------------------------------
     65.2   20,318,348,211     12,196  1,665,984.6      3,806.0     1,713  143,905,820  4,877,424.6  cudaStreamSynchronize                     
     19.6    6,114,479,110    979,090      6,245.1      4,893.0       826   61,317,707    103,504.7  cudaLaunchKernel                          
      5.9    1,844,232,020    151,960     12,136.3      9,991.0     7,437    6,397,280     55,443.5  cudaGraphLaunch_v10000                    
      4.4    1,366,270,456     61,593     22,182.2      8,605.0     2,898   97,438,741    427,651.1  cudaMemcpyAsync                           
      2.1      657,913,070    123,014      5,348.3      4,791.0       646   11,218,430     74,172.4  cuLaunchKernel                            
      0.7      225,191,175      1,943    115,898.7     75,223.0    40,921    1,507,774    191,247.4  cudaGraphInstantiateWithFlags_v11040      
      0.6      190,028,321      2,135     89,006.2     32,930.0     5,778  121,430,749  2,627,383.4  cudaDeviceSynchronize                     
      0.4      131,733,072     24,728      5,327.3      5,346.0       183    7,263,692     48,804.8  cudaMemsetAsync                           
      0.4      117,166,497    154,261        759.5        737.0       297        9,955        164.6  cudaStreamIsCapturing_v10000              
      0.2       54,817,946        222    246,927.7    125,544.5    64,964    2,389,846    359,442.8  cudaFree                                  
      0.1       41,574,143        348    119,465.9    111,957.5     6,496    1,314,648     70,124.0  cudaMalloc                                
      0.1       25,470,407         10  2,547,040.7  2,568,202.0    60,182    4,674,895  1,473,736.1  cuLibraryLoadData                         
      0.0       14,126,639     13,502      1,046.3        512.0       267    4,070,645     36,594.4  cuKernelGetFunction                       
      0.0       11,511,739        169     68,116.8     73,800.0    26,538      398,968     40,288.3  cuModuleLoadData                          
      0.0        9,477,345     18,895        501.6        477.0       305        7,151        120.4  cudaStreamGetCaptureInfo_v2_v11030        
      0.0        8,547,159      1,943      4,398.9      4,349.0     3,274       12,306        644.1  cudaStreamBeginCapture_v10000             
      0.0        7,583,507      1,943      3,903.0      3,886.0     2,371       10,115        530.0  cudaGraphDestroy_v10000                   
      0.0        2,953,354        128     23,073.1      2,127.0     1,339      976,651    118,496.6  cudaStreamCreateWithPriority              
      0.0        2,583,759      1,943      1,329.8      1,322.0       973        2,362        129.3  cudaStreamEndCapture_v10000               
      0.0        1,910,887         26     73,495.7     12,773.5     3,625    1,207,162    232,915.8  cudaHostAlloc                             
      0.0        1,625,828      1,943        836.8        771.0       625        3,016        254.6  cudaGraphGetNodes_v10000                  
      0.0          943,862        310      3,044.7      2,639.0       879       11,991      1,944.4  cudaEventQuery                            
      0.0          731,374        311      2,351.7      2,439.0       991        7,657      1,133.3  cudaEventRecord                           
      0.0          219,541          8     27,442.6     26,305.5     8,804       64,233     18,995.2  cudaMemGetInfo                            
      0.0          140,500        810        173.5        143.0        85        1,704        110.6  cuGetProcAddress_v2                       
      0.0           21,914         21      1,043.5        438.0       339        4,729      1,202.9  cudaEventCreateWithFlags                  
      0.0           16,258         16      1,016.1        849.5       502        2,663        551.3  cuLibraryGetKernel                        
      0.0            8,991         14        642.2        586.0       346        1,420        261.0  cudaThreadExchangeStreamCaptureMode_v10010
      0.0            4,849          3      1,616.3      1,664.0     1,386        1,799        210.6  cuInit                                    
      0.0            3,460          4        865.0        749.0       110        1,852        882.7  cuModuleGetLoadingMode                    
      0.0            3,416          1      3,416.0      3,416.0     3,416        3,416          0.0  cudaStreamWaitEvent                       
      0.0            1,901          1      1,901.0      1,901.0     1,901        1,901          0.0  cudaEventDestroy                          
      0.0            1,166          2        583.0        583.0       248          918        473.8  cudaGetDriverEntryPoint_v11030            

[6/8] Executing 'cuda_gpu_kern_sum' stats report

 Time (%)  Total Time (ns)  Instances   Avg (ns)     Med (ns)    Min (ns)   Max (ns)   StdDev (ns)                                                  Name                                                
 --------  ---------------  ---------  -----------  -----------  ---------  ---------  -----------  ----------------------------------------------------------------------------------------------------
     33.5    9,507,682,829     84,588    112,399.9     58,880.0      5,728    569,477    137,306.6  void flash::flash_fwd_splitkv_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (int)4, (…
     27.2    7,733,720,607     29,164    265,180.4    333,123.0     33,344    763,622    112,810.5  ampere_bf16_s1688gemm_bf16_64x128_sliced1x2_ldg8_f2f_tn                                             
      7.4    2,089,759,636      1,164  1,795,326.1  1,390,859.0     40,065  4,518,698  1,024,759.1  ampere_bf16_s1688gemm_bf16_128x128_ldg8_f2f_stages_32x1_tn                                          
      3.3      942,739,585      5,754    163,840.7     13,376.0      1,951  1,008,234    293,922.8  void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIterator…
      3.3      942,069,183     76,664     12,288.3      8,032.0      6,240     73,248      8,482.6  void flash::flash_fwd_splitkv_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (int)4, (…
      3.3      926,915,977      5,958    155,575.0     73,120.5      7,649    549,540    194,687.6  void cutlass::Kernel2<cutlass_80_tensorop_bf16_s16816gemm_relu_bf16_64x64_32x6_tn_align8>(T1::Param…
      2.8      781,701,830      1,991    392,617.7    496,547.0     10,528    506,724    194,713.8  void cutlass::Kernel2<cutlass_80_wmma_tensorop_bf16_s161616gemm_bf16_16x16_128x2_tn_align8>(T1::Par…
      2.5      718,309,736      5,756    124,793.2      9,920.0      5,151    716,420    213,447.3  void at::native::reduce_kernel<(int)512, (int)1, at::native::ReduceOp<float, at::native::ArgMaxOps<…
      2.4      679,170,209    292,768      2,319.8      1,889.0      1,631      6,304        962.1  void at::native::elementwise_kernel<(int)128, (int)4, void at::native::gpu_kernel_impl_nocast<at::n…
      2.1      605,586,081     14,252     42,491.3     42,529.0     26,240     62,817      1,642.0  ampere_bf16_s1688gemm_bf16_128x64_sliced1x2_ldg8_relu_f2f_tn                                        
      1.8      516,743,427     13,776     37,510.4     37,472.0     36,608     42,560        332.8  ampere_bf16_s1688gemm_bf16_64x64_sliced1x4_ldg8_f2f_tn                                              
      1.3      366,625,152     16,268     22,536.6     23,936.0      1,055    462,659     19,521.4  triton_poi_fused_mul_silu_1                                                                         
      1.2      345,171,402        112  3,081,887.5  3,078,316.5  3,036,028  3,128,477     29,283.9  void flash::flash_fwd_splitkv_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (int)4, (…
      0.9      260,532,523        513    507,860.7    507,843.0    506,403    509,475        427.2  void cutlass::Kernel2<cutlass_80_wmma_tensorop_bf16_s161616gemm_bf16_16x16_128x1_tn_align8>(T1::Par…
      0.9      255,622,286        604    423,215.7    487,970.0      7,008    488,866    160,519.3  std::enable_if<!T7, void>::type internal::gemvx::kernel<int, int, __nv_bfloat16, __nv_bfloat16, __n…
      0.9      242,493,430    161,056      1,505.6      1,280.0      1,023      3,488        458.1  void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0…
      0.7      206,425,050    146,384      1,410.2      1,344.0      1,183      2,208        221.6  void at::native::elementwise_kernel<(int)128, (int)2, void at::native::gpu_kernel_impl_nocast<at::n…
      0.7      203,499,133        184  1,105,973.5    579,541.0    369,795  2,808,909    981,858.0  ampere_bf16_s16816gemm_bf16_128x64_ldg8_f2f_tn                                                      
      0.7      187,786,954      1,120    167,666.9    158,929.0     40,416  1,415,463    206,084.0  ampere_bf16_s1688gemm_bf16_128x64_sliced1x2_ldg8_f2f_tn                                             
      0.6      180,432,004     16,268     11,091.2     11,936.0      1,505    111,617      4,905.8  triton_red_fused__to_copy_add_mean_mul_pow_rsqrt_2                                                  
      0.5      135,678,243     43,792      3,098.2      3,104.0      2,943      3,616         73.3  void flash::flash_fwd_splitkv_combine_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (…
      0.3       98,055,325     32,872      2,982.9      2,945.0      2,847      3,233         98.3  void flash::flash_fwd_splitkv_combine_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (…
      0.3       83,656,872     16,268      5,142.4      5,472.0      1,536     79,136      3,233.8  triton_red_fused__to_copy_add_mean_mul_pow_rsqrt_0                                                  
      0.2       52,052,585     15,687      3,318.2      3,457.0      1,344     22,048        905.0  triton_poi_fused_cat_3                                                                              
      0.1       39,252,777          8  4,906,597.1  4,863,769.0  4,802,745  5,085,370    117,043.6  void at_cuda_detail::cub::DeviceSegmentedRadixSortKernel<at_cuda_detail::cub::DeviceRadixSortPolicy…
      0.1       35,101,287     15,687      2,237.6      2,336.0        863     16,672        687.2  triton_poi_fused_view_5                                                                             
      0.1       26,987,031     17,256      1,563.9      1,408.0      1,023      2,784        465.1  void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIterator…
      0.1       22,634,043        784     28,870.0     12,543.5     11,616     62,720     20,595.1  ampere_bf16_s16816gemm_bf16_64x64_ldg8_f2f_stages_64x5_tn                                           
      0.1       22,584,985     15,687      1,439.7      1,440.0      1,215      6,720        194.4  triton_poi_fused_cat_4                                                                              
      0.1       20,606,081      5,888      3,499.7      3,136.0      2,687      7,488        970.6  void at::native::index_elementwise_kernel<(int)128, (int)4, void at::native::gpu_index_kernel<void …
      0.1       20,451,721          4  5,112,930.3  5,112,153.5  4,937,754  5,289,660    201,308.2  void at_cuda_detail::cub::DeviceSegmentedRadixSortKernel<at_cuda_detail::cub::DeviceRadixSortPolicy…
      0.1       15,066,944      5,752      2,619.4      2,368.0      1,952      3,969        554.4  void at::native::index_elementwise_kernel<(int)128, (int)4, void at::native::gpu_index_kernel<void …
      0.1       14,293,381         28    510,477.9    512,002.5    468,706    513,474      8,208.5  void at::native::vectorized_elementwise_kernel<(int)4, at::native::FillFunctor<signed char>, std::a…
      0.0        9,733,874          4  2,433,468.5  2,435,244.5  2,367,692  2,495,693     60,628.3  void at::native::<unnamed>::cunn_SoftMaxForward<(int)4, float, float, float, at::native::<unnamed>:…
      0.0        9,136,049         28    326,287.5    326,210.0    324,514    329,538        982.3  ampere_bf16_s1688gemm_bf16_128x128_ldg8_relu_f2f_stages_32x1_tn                                     
      0.0        8,425,678        224     37,614.6     37,568.5     36,608     38,880        409.5  void cutlass::Kernel2<cutlass_80_tensorop_bf16_s16816gemm_relu_bf16_64x128_32x6_tn_align8>(T1::Para…
      0.0        7,777,256          2  3,888,628.0  3,888,628.0  3,705,715  4,071,541    258,678.0  void at::native::_scatter_gather_elementwise_kernel<(int)128, (int)8, void at::native::_cuda_scatte…
      0.0        7,758,429      8,970        864.9        864.0        767      1,280         77.7  void at::native::vectorized_elementwise_kernel<(int)2, at::native::FillFunctor<long>, std::array<ch…
      0.0        7,519,688      5,754      1,306.9      1,152.0      1,023      2,048        279.6  void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIterator…
      0.0        7,231,396        336     21,522.0     21,440.0     21,056     22,592        362.7  ampere_bf16_s16816gemm_bf16_128x64_ldg8_relu_f2f_stages_64x3_tn                                     
      0.0        6,130,365        476     12,878.9     12,800.5     11,744     14,432        645.4  ampere_bf16_s16816gemm_bf16_64x64_ldg8_relu_f2f_stages_64x5_tn                                      
      0.0        5,896,061          4  1,474,015.3  1,473,463.0  1,473,191  1,475,944      1,292.3  void at::native::vectorized_elementwise_kernel<(int)4, at::native::<unnamed>::masked_fill_kernel(at…
      0.0        5,380,367      5,752        935.4        896.0        863      1,344         76.3  void at::native::unrolled_elementwise_kernel<at::native::CUDAFunctorOnSelf_add<int>, std::array<cha…
      0.0        4,603,692      5,292        869.9        864.0        767      1,185         33.2  void at::native::unrolled_elementwise_kernel<at::native::FillFunctor<int>, std::array<char *, (unsi…
      0.0        3,996,949          2  1,998,474.5  1,998,474.5  1,996,490  2,000,459      2,806.5  void at::native::vectorized_elementwise_kernel<(int)4, at::native::BinaryFunctor<float, float, floa…
      0.0        3,842,156      4,143        927.4        896.0        800      1,856         93.0  void at::native::vectorized_elementwise_kernel<(int)4, at::native::FillFunctor<int>, std::array<cha…
      0.0        3,593,747         56     64,174.1     64,144.5     63,105     65,728        478.5  void cutlass::Kernel2<cutlass_80_wmma_tensorop_bf16_s161616gemm_bf16_32x32_64x1_tn_align8>(T1::Para…
      0.0        3,433,971          4    858,492.8    858,901.0    855,877    860,292      2,168.9  void at::native::elementwise_kernel<(int)128, (int)4, void at::native::gpu_kernel_impl_nocast<at::n…
      0.0        3,191,215          2  1,595,607.5  1,595,607.5  1,560,359  1,630,856     49,848.9  void at::native::tensor_kernel_scan_innermost_dim<float, std::plus<float>>(T1 *, const T1 *, unsign…
      0.0        2,871,002      1,512      1,898.8      1,760.0      1,312      2,912        445.3  void cublasLt::splitKreduce_kernel<(int)32, (int)16, int, __nv_bfloat16, __nv_bfloat16, float, (boo…
      0.0        2,643,071        581      4,549.2      4,671.0      1,984     36,256      1,427.2  triton_red_fused__to_copy_add_embedding_mean_mul_pow_rsqrt_0                                        
      0.0        2,581,742          2  1,290,871.0  1,290,871.0  1,290,663  1,291,079        294.2  at::native::<unnamed>::fill_reverse_indices_kernel(long *, int, at::cuda::detail::IntDivider<unsign…
      0.0        2,581,389          2  1,290,694.5  1,290,694.5  1,290,406  1,290,983        408.0  void at::native::elementwise_kernel<(int)128, (int)2, void at::native::gpu_kernel_impl_nocast<at::n…
      0.0        2,421,998        112     21,625.0     21,552.0      9,408     34,465     12,020.4  void cutlass::Kernel2<cutlass_80_wmma_tensorop_bf16_s161616gemm_bf16_32x32_128x2_tn_align8>(T1::Par…
      0.0        1,835,794        581      3,159.7      3,200.0      1,632     39,200      1,543.9  triton_poi_fused_cat_1                                                                              
      0.0        1,365,128          2    682,564.0    682,564.0    677,764    687,364      6,788.2  void at::native::<unnamed>::distribution_elementwise_grid_stride_kernel<float, (int)4, void at::nat…
      0.0        1,304,994        581      2,246.1      2,368.0        863     14,272        629.4  triton_poi_fused_view_3                                                                             
      0.0        1,202,982         56     21,481.8     21,456.0     21,152     21,888        275.5  ampere_bf16_s16816gemm_bf16_128x64_ldg8_f2f_stages_32x6_tn                                          
      0.0        1,027,854      1,153        891.5        896.0        800      1,216         36.7  void at::native::vectorized_elementwise_kernel<(int)2, at::native::FillFunctor<int>, std::array<cha…
      0.0          956,098         28     34,146.4     34,736.5     17,920     35,200      3,188.0  std::enable_if<!T7, void>::type internal::gemvx::kernel<int, int, __nv_bfloat16, float, float, floa…
      0.0          847,695        581      1,459.0      1,440.0      1,216      9,408        336.4  triton_poi_fused_cat_2                                                                              
      0.0          611,794        673        909.1        896.0        864      1,025         28.1  void at::native::unrolled_elementwise_kernel<at::native::FillFunctor<long>, std::array<char *, (uns…
      0.0          417,574        308      1,355.8      1,344.0      1,311      1,504         21.9  void vllm::merge_attn_states_kernel<__nv_bfloat16, (unsigned int)128>(T1 *, float *, const T1 *, co…
      0.0          295,335        168      1,757.9      1,760.0      1,535      2,080        119.1  void cublasLt::splitKreduce_kernel<(int)32, (int)16, int, __nv_bfloat16, __nv_bfloat16, float, (boo…
      0.0          155,841          1    155,841.0    155,841.0    155,841    155,841          0.0  void at::native::<unnamed>::CatArrayBatchedCopy_aligned16_contig<at::native::<unnamed>::OpaqueType<…
      0.0           78,880          1     78,880.0     78,880.0     78,880     78,880          0.0  void at::native::vectorized_elementwise_kernel<(int)4, at::native::bfloat16_copy_kernel_cuda(at::Te…
      0.0           63,740         58      1,099.0        896.0        864     11,360      1,372.6  void at::native::vectorized_elementwise_kernel<(int)4, at::native::FillFunctor<c10::BFloat16>, std:…
      0.0           43,936          1     43,936.0     43,936.0     43,936     43,936          0.0  void at::native::vectorized_elementwise_kernel<(int)4, at::native::sin_kernel_cuda(at::TensorIterat…
      0.0           36,570         28      1,306.1      1,312.0      1,280      1,376         19.5  void cublasLt::splitKreduce_kernel<(int)32, (int)16, int, float, __nv_bfloat16, float, (bool)0, __n…
      0.0           26,816          1     26,816.0     26,816.0     26,816     26,816          0.0  void at::native::vectorized_elementwise_kernel<(int)4, at::native::cos_kernel_cuda(at::TensorIterat…
      0.0           19,520          1     19,520.0     19,520.0     19,520     19,520          0.0  void at::native::elementwise_kernel<(int)128, (int)2, void at::native::gpu_kernel_impl_nocast<at::n…
      0.0           11,936         11      1,085.1        864.0        864      1,568        286.4  void at::native::vectorized_elementwise_kernel<(int)4, at::native::FillFunctor<float>, std::array<c…
      0.0           10,752          2      5,376.0      5,376.0      5,120      5,632        362.0  void at::native::_scatter_gather_elementwise_kernel<(int)128, (int)8, void at::native::_cuda_scatte…
      0.0            9,152          2      4,576.0      4,576.0      4,480      4,672        135.8  void at::native::<unnamed>::distribution_elementwise_grid_stride_kernel<float, (int)4, void at::nat…
      0.0            3,616          2      1,808.0      1,808.0      1,600      2,016        294.2  void at::native::elementwise_kernel<(int)128, (int)4, void at::native::gpu_kernel_impl_nocast<at::n…
      0.0            3,424          2      1,712.0      1,712.0      1,664      1,760         67.9  void at::native::vectorized_elementwise_kernel<(int)2, at::native::CUDAFunctorOnOther_add<long>, st…
      0.0            3,136          2      1,568.0      1,568.0      1,504      1,632         90.5  void at::native::vectorized_elementwise_kernel<(int)2, at::native::<unnamed>::where_kernel_impl(at:…
      0.0            3,104          2      1,552.0      1,552.0      1,344      1,760        294.2  void at::native::vectorized_elementwise_kernel<(int)4, void at::native::compare_scalar_kernel<float…
      0.0            2,975          2      1,487.5      1,487.5        992      1,983        700.7  void <unnamed>::elementwise_kernel_with_index<int, at::native::arange_cuda_out(const c10::Scalar &,…
      0.0            2,912          2      1,456.0      1,456.0      1,344      1,568        158.4  void at::native::vectorized_elementwise_kernel<(int)4, at::native::CUDAFunctorOnOther_add<float>, s…
      0.0            2,336          1      2,336.0      2,336.0      2,336      2,336          0.0  void at::native::elementwise_kernel<(int)128, (int)4, void at::native::gpu_kernel_impl<at::native::…
      0.0            1,184          1      1,184.0      1,184.0      1,184      1,184          0.0  void at::native::vectorized_elementwise_kernel<(int)4, at::native::reciprocal_kernel_cuda(at::Tenso…
      0.0            1,024          1      1,024.0      1,024.0      1,024      1,024          0.0  void at::native::vectorized_elementwise_kernel<(int)4, at::native::AUnaryFunctor<float, float, floa…
      0.0            1,024          1      1,024.0      1,024.0      1,024      1,024          0.0  void at::native::vectorized_elementwise_kernel<(int)4, at::native::BUnaryFunctor<float, float, floa…
      0.0              896          1        896.0        896.0        896        896          0.0  void at::native::vectorized_elementwise_kernel<(int)2, at::native::FillFunctor<double>, std::array<…

[7/8] Executing 'cuda_gpu_mem_time_sum' stats report

 Time (%)  Total Time (ns)  Count   Avg (ns)  Med (ns)  Min (ns)   Max (ns)   StdDev (ns)            Operation           
 --------  ---------------  ------  --------  --------  --------  ----------  -----------  ------------------------------
     93.2      540,571,743  41,277  13,096.2     352.0       287  97,068,545    513,408.1  [CUDA memcpy Host-to-Device]  
      3.2       18,710,334  14,564   1,284.7     896.0       864   1,362,855     22,521.7  [CUDA memcpy Device-to-Device]
      2.5       14,536,294  21,760     668.0     768.0       287       7,744        311.5  [CUDA memset]                 
      1.1        6,503,130   5,752   1,130.6   1,120.0       863       1,760         95.6  [CUDA memcpy Device-to-Host]  

[8/8] Executing 'cuda_gpu_mem_size_sum' stats report

 Total (MB)  Count   Avg (MB)  Med (MB)  Min (MB)  Max (MB)  StdDev (MB)            Operation           
 ----------  ------  --------  --------  --------  --------  -----------  ------------------------------
  4,190.741  41,277     0.102     0.000     0.000   466.747        2.619  [CUDA memcpy Host-to-Device]  
  2,534.048  14,564     0.174     0.003     0.003   622.330       10.312  [CUDA memcpy Device-to-Device]
     14.589  21,760     0.001     0.001     0.000     0.006        0.000  [CUDA memset]                 
      4.192   5,752     0.001     0.000     0.000     0.004        0.001  [CUDA memcpy Device-to-Host]  

Generated:
    /data/cy/kv_cache_vs_util/sim_traverse_bs/traverse_bs_util_sim_decoding.nsys-rep
    /data/cy/kv_cache_vs_util/sim_traverse_bs/traverse_bs_util_sim_decoding.sqlite