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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 19:02:19 [__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: ['prefill640_decode512']
------------------------------------------------------------
加载分词器/模型中...
INFO 08-13 19:02:29 [config.py:1604] Using max model len 4096
INFO 08-13 19:02:29 [config.py:2434] Chunked prefill is enabled with max_num_batched_tokens=8192.
INFO 08-13 19:02:35 [__init__.py:235] Automatically detected platform cuda.
INFO 08-13 19:02:37 [core.py:572] Waiting for init message from front-end.
INFO 08-13 19:02:37 [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 19:02:40 [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 19:02:40 [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 19:02:40 [gpu_model_runner.py:1843] Starting to load model Qwen/Qwen2-1.5B...
INFO 08-13 19:02:40 [gpu_model_runner.py:1875] Loading model from scratch...
INFO 08-13 19:02:40 [cuda.py:290] Using Flash Attention backend on V1 engine.
INFO 08-13 19:02:40 [weight_utils.py:296] Using model weights format ['*.safetensors']
INFO 08-13 19:02:41 [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, 1.54it/s]
Loading safetensors checkpoint shards: 100% Completed | 1/1 [00:00<00:00, 1.54it/s]
INFO 08-13 19:02:42 [default_loader.py:262] Loading weights took 0.75 seconds
INFO 08-13 19:02:42 [gpu_model_runner.py:1892] Model loading took 2.9105 GiB and 1.965894 seconds
INFO 08-13 19:02:48 [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 19:02:48 [backends.py:541] Dynamo bytecode transform time: 6.08 s
INFO 08-13 19:02:53 [backends.py:194] Cache the graph for dynamic shape for later use
INFO 08-13 19:03:14 [backends.py:215] Compiling a graph for dynamic shape takes 25.33 s
INFO 08-13 19:03:21 [monitor.py:34] torch.compile takes 31.41 s in total
INFO 08-13 19:03:22 [gpu_worker.py:255] Available KV cache memory: 12.80 GiB
INFO 08-13 19:03:22 [kv_cache_utils.py:833] GPU KV cache size: 479,456 tokens
INFO 08-13 19:03:22 [kv_cache_utils.py:837] Maximum concurrency for 4,096 tokens per request: 117.05x
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, 33.90it/s]
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Capturing CUDA graph shapes: 78%|███████▊ | 52/67 [00:01<00:00, 33.31it/s]
Capturing CUDA graph shapes: 84%|████████▎ | 56/67 [00:01<00:00, 32.69it/s]
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Capturing CUDA graph shapes: 96%|█████████▌| 64/67 [00:01<00:00, 32.14it/s]
Capturing CUDA graph shapes: 100%|██████████| 67/67 [00:02<00:00, 32.94it/s]
INFO 08-13 19:03:25 [gpu_model_runner.py:2485] Graph capturing finished in 2 secs, took 0.49 GiB
INFO 08-13 19:03:25 [core.py:193] init engine (profile, create kv cache, warmup model) took 42.37 seconds
模型加载完成。
===== 场景：prefill640_decode512 | prefill=640, decode=512 =====
--- 批量大小 bs=1 ---
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Processed prompts: 100%|██████████| 1/1 [00:03<00:00, 3.33s/it, est. speed input: 192.34 toks/s, output: 153.87 toks/s]
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执行时间: 3.3360 s
实际平均输入 tokens: 640.00（目标 640）
生成总 tokens: 512
吞吐(生成tokens/秒): 153.48
TTFT (V1 metrics): 0.0327 s
解码吞吐 (V1 metrics): 154.93 tok/s
--- 批量大小 bs=2 ---
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执行时间: 3.7300 s
实际平均输入 tokens: 640.00（目标 640）
生成总 tokens: 1024
吞吐(生成tokens/秒): 274.53
TTFT (V1 metrics): 0.0158 s
解码吞吐 (V1 metrics): 137.84 tok/s
--- 批量大小 bs=4 ---
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执行时间: 3.6164 s
实际平均输入 tokens: 640.00（目标 640）
生成总 tokens: 2048
吞吐(生成tokens/秒): 566.30
TTFT (V1 metrics): 0.0169 s
解码吞吐 (V1 metrics): 142.63 tok/s
--- 批量大小 bs=8 ---
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Adding requests: 100%|██████████| 8/8 [00:00<00:00, 244.30it/s]
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Processed prompts: 100%|██████████| 8/8 [00:03<00:00, 3.66s/it, est. speed input: 1386.86 toks/s, output: 1109.48 toks/s]
Processed prompts: 100%|██████████| 8/8 [00:03<00:00, 2.17it/s, est. speed input: 1386.86 toks/s, output: 1109.48 toks/s]
执行时间: 3.7265 s
实际平均输入 tokens: 640.00（目标 640）
生成总 tokens: 4096
吞吐(生成tokens/秒): 1099.15
TTFT (V1 metrics): 0.0219 s
解码吞吐 (V1 metrics): 138.89 tok/s
--- 批量大小 bs=16 ---
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执行时间: 3.8919 s
实际平均输入 tokens: 640.00（目标 640）
生成总 tokens: 8192
吞吐(生成tokens/秒): 2104.89
TTFT (V1 metrics): 0.0329 s
解码吞吐 (V1 metrics): 133.82 tok/s
--- 批量大小 bs=32 ---
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执行时间: 4.0341 s
实际平均输入 tokens: 640.00（目标 640）
生成总 tokens: 16384
吞吐(生成tokens/秒): 4061.41
TTFT (V1 metrics): 0.0461 s
解码吞吐 (V1 metrics): 130.12 tok/s
--- 批量大小 bs=64 ---
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执行时间: 4.4199 s
实际平均输入 tokens: 640.00（目标 640）
生成总 tokens: 32768
吞吐(生成tokens/秒): 7413.77
TTFT (V1 metrics): 0.0691 s
解码吞吐 (V1 metrics): 120.00 tok/s
--- 批量大小 bs=128 ---
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Processed prompts: 100%|██████████| 128/128 [00:06<00:00, 21.94it/s, est. speed input: 13606.51 toks/s, output: 10866.05 toks/s]
Processed prompts: 100%|██████████| 128/128 [00:06<00:00, 21.26it/s, est. speed input: 13606.51 toks/s, output: 10866.05 toks/s]
执行时间: 6.2947 s
实际平均输入 tokens: 640.00（目标 640）
生成总 tokens: 65421
吞吐(生成tokens/秒): 10393.02
TTFT (V1 metrics): 0.1218 s
解码吞吐 (V1 metrics): 84.64 tok/s
--- 批量大小 bs=256 ---
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Processed prompts: 100%|██████████| 256/256 [00:08<00:00, 30.12it/s, est. speed input: 19279.66 toks/s, output: 15423.69 toks/s]
执行时间: 9.2625 s
实际平均输入 tokens: 640.00（目标 640）
生成总 tokens: 131072
吞吐(生成tokens/秒): 14150.76
TTFT (V1 metrics): 0.4813 s
解码吞吐 (V1 metrics): 59.00 tok/s
--- 批量大小 bs=512 ---
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Processed prompts: 60%|██████ | 309/512 [00:13<00:01, 194.95it/s, est. speed input: 15165.00 toks/s, output: 12131.95 toks/s]
Processed prompts: 83%|████████▎ | 424/512 [00:13<00:00, 334.87it/s, est. speed input: 20649.39 toks/s, output: 16519.45 toks/s]
Processed prompts: 100%|██████████| 512/512 [00:13<00:00, 334.87it/s, est. speed input: 24865.42 toks/s, output: 19892.30 toks/s]
Processed prompts: 100%|██████████| 512/512 [00:13<00:00, 38.85it/s, est. speed input: 24865.42 toks/s, output: 19892.30 toks/s]
执行时间: 14.1481 s
实际平均输入 tokens: 640.00（目标 640）
生成总 tokens: 262144
吞吐(生成tokens/秒): 18528.59
TTFT (V1 metrics): 0.4908 s
解码吞吐 (V1 metrics): 38.46 tok/s
--- 批量大小 bs=1024 ---
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Adding requests: 10%|█ | 104/1024 [00:00<00:01, 519.20it/s]
Adding requests: 16%|█▌ | 161/1024 [00:00<00:01, 538.78it/s]
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Adding requests: 27%|██▋ | 272/1024 [00:00<00:01, 543.49it/s]
Adding requests: 32%|███▏ | 329/1024 [00:00<00:01, 549.44it/s]
Adding requests: 38%|███▊ | 386/1024 [00:00<00:01, 554.88it/s]
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Adding requests: 71%|███████ | 727/1024 [00:01<00:00, 561.74it/s]
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Adding requests: 100%|██████████| 1024/1024 [00:01<00:00, 551.71it/s]
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Processed prompts: 0%| | 3/1024 [00:22<1:41:29, 5.96s/it, est. speed input: 83.63 toks/s, output: 66.91 toks/s]
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Processed prompts: 1%| | 9/1024 [00:23<21:24, 1.27s/it, est. speed input: 247.84 toks/s, output: 198.27 toks/s]
Processed prompts: 2%|▏ | 18/1024 [00:23<07:12, 2.32it/s, est. speed input: 493.23 toks/s, output: 394.58 toks/s]
Processed prompts: 3%|▎ | 29/1024 [00:23<03:23, 4.89it/s, est. speed input: 790.76 toks/s, output: 632.60 toks/s]
Processed prompts: 4%|▍ | 41/1024 [00:23<01:53, 8.65it/s, est. speed input: 1112.40 toks/s, output: 889.92 toks/s]
Processed prompts: 5%|▌ | 53/1024 [00:23<01:11, 13.55it/s, est. speed input: 1430.98 toks/s, output: 1144.78 toks/s]
Processed prompts: 6%|▋ | 65/1024 [00:23<00:48, 19.81it/s, est. speed input: 1746.99 toks/s, output: 1397.59 toks/s]
Processed prompts: 8%|▊ | 78/1024 [00:23<00:33, 28.26it/s, est. speed input: 2086.88 toks/s, output: 1669.50 toks/s]
Processed prompts: 9%|▉ | 97/1024 [00:24<00:21, 44.07it/s, est. speed input: 2583.51 toks/s, output: 2066.80 toks/s]
Processed prompts: 11%|█ | 113/1024 [00:24<00:15, 58.03it/s, est. speed input: 2996.43 toks/s, output: 2397.14 toks/s]
Processed prompts: 12%|█▎ | 128/1024 [00:24<00:12, 71.27it/s, est. speed input: 3379.49 toks/s, output: 2703.59 toks/s]
Processed prompts: 14%|█▍ | 144/1024 [00:24<00:10, 85.72it/s, est. speed input: 3785.19 toks/s, output: 3028.14 toks/s]
Processed prompts: 16%|█▌ | 161/1024 [00:24<00:08, 101.40it/s, est. speed input: 4213.87 toks/s, output: 3371.09 toks/s]
Processed prompts: 17%|█▋ | 176/1024 [00:24<00:07, 111.44it/s, est. speed input: 4587.23 toks/s, output: 3669.78 toks/s]
Processed prompts: 19%|█▉ | 194/1024 [00:24<00:06, 127.67it/s, est. speed input: 5035.86 toks/s, output: 4028.68 toks/s]
Processed prompts: 22%|██▏ | 225/1024 [00:24<00:05, 156.64it/s, est. speed input: 5806.81 toks/s, output: 4645.44 toks/s]
Processed prompts: 24%|██▍ | 249/1024 [00:24<00:04, 176.31it/s, est. speed input: 6399.91 toks/s, output: 5119.91 toks/s]
Processed prompts: 28%|██▊ | 287/1024 [00:25<00:03, 212.13it/s, est. speed input: 7338.05 toks/s, output: 5870.43 toks/s]
Processed prompts: 32%|███▏ | 331/1024 [00:25<00:02, 251.91it/s, est. speed input: 8419.80 toks/s, output: 6735.82 toks/s]
Processed prompts: 38%|███▊ | 390/1024 [00:25<00:01, 321.26it/s, est. speed input: 9873.47 toks/s, output: 7898.76 toks/s]
Processed prompts: 44%|████▍ | 450/1024 [00:25<00:01, 372.36it/s, est. speed input: 11338.05 toks/s, output: 9070.42 toks/s]
Processed prompts: 50%|█████ | 512/1024 [00:25<00:01, 435.95it/s, est. speed input: 12849.49 toks/s, output: 10279.57 toks/s]
Processed prompts: 60%|█████▉ | 612/1024 [00:25<00:00, 571.12it/s, est. speed input: 15292.72 toks/s, output: 12234.15 toks/s]
Processed prompts: 95%|█████████▌| 976/1024 [00:25<00:00, 1391.11it/s, est. speed input: 24289.89 toks/s, output: 19431.89 toks/s]
Processed prompts: 100%|██████████| 1024/1024 [00:25<00:00, 1391.11it/s, est. speed input: 25307.94 toks/s, output: 20246.33 toks/s]
Processed prompts: 100%|██████████| 1024/1024 [00:25<00:00, 39.54it/s, est. speed input: 25307.94 toks/s, output: 20246.33 toks/s]
[rank0]:[W813 19:04:51.071947265 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: 27.7908 s
实际平均输入 tokens: 640.00（目标 640）
生成总 tokens: 524288
吞吐(生成tokens/秒): 18865.49
TTFT (V1 metrics): 0.9638 s
解码吞吐 (V1 metrics): 19.72 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-e7ae.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
-------- --------------- --------- ---------------- ---------------- -------------- -------------- ----------- ------- ----------------------------------------
43.1 63,806,267,138 1 63,806,267,138.0 63,806,267,138.0 63,806,267,138 63,806,267,138 0.0 PushPop :LLM_init
18.8 27,790,304,411 1 27,790,304,411.0 27,790,304,411.0 27,790,304,411 27,790,304,411 0.0 PushPop :generate [prefill640_decode512] bs=1024
9.6 14,147,468,287 1 14,147,468,287.0 14,147,468,287.0 14,147,468,287 14,147,468,287 0.0 PushPop :generate [prefill640_decode512] bs=512
6.3 9,262,392,366 1 9,262,392,366.0 9,262,392,366.0 9,262,392,366 9,262,392,366 0.0 PushPop :generate [prefill640_decode512] bs=256
4.3 6,294,556,076 1 6,294,556,076.0 6,294,556,076.0 6,294,556,076 6,294,556,076 0.0 PushPop :generate [prefill640_decode512] bs=128
3.0 4,419,734,921 1 4,419,734,921.0 4,419,734,921.0 4,419,734,921 4,419,734,921 0.0 PushPop :generate [prefill640_decode512] bs=64
2.7 4,033,922,062 1 4,033,922,062.0 4,033,922,062.0 4,033,922,062 4,033,922,062 0.0 PushPop :generate [prefill640_decode512] bs=32
2.6 3,891,757,396 1 3,891,757,396.0 3,891,757,396.0 3,891,757,396 3,891,757,396 0.0 PushPop :generate [prefill640_decode512] bs=16
2.5 3,729,817,085 1 3,729,817,085.0 3,729,817,085.0 3,729,817,085 3,729,817,085 0.0 PushPop :generate [prefill640_decode512] bs=2
2.5 3,726,348,651 1 3,726,348,651.0 3,726,348,651.0 3,726,348,651 3,726,348,651 0.0 PushPop :generate [prefill640_decode512] bs=8
2.4 3,616,307,172 1 3,616,307,172.0 3,616,307,172.0 3,616,307,172 3,616,307,172 0.0 PushPop :generate [prefill640_decode512] bs=4
2.3 3,335,871,818 1 3,335,871,818.0 3,335,871,818.0 3,335,871,818 3,335,871,818 0.0 PushPop :generate [prefill640_decode512] bs=1
0.0 88,217 2 44,108.5 44,108.5 42,206 46,011 2,690.5 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
-------- ----------------- --------- --------------- ---------------- --------- --------------- --------------- ----------------------
30.2 1,744,937,975,193 54,559 31,982,587.2 36,252.0 1,000 131,944,469,826 1,264,387,583.2 pthread_cond_timedwait
24.4 1,409,850,293,508 90,937 15,503,593.6 10,063,900.0 1,000 89,656,403,165 542,281,129.3 epoll_wait
24.3 1,405,293,461,182 2,062 681,519,622.3 169,137.0 1,777 131,946,128,306 9,309,452,118.6 pthread_cond_wait
8.2 470,649,973,426 67 7,024,626,469.0 10,000,075,590.0 8,879 10,000,128,605 4,563,470,551.8 sem_timedwait
7.6 440,451,323,826 42,747 10,303,678.0 1,400.0 1,000 13,214,170,856 151,629,150.0 poll
2.6 148,761,603,454 44,756 3,323,836.0 2,218.0 1,000 130,016,250,506 617,021,890.8 read
2.4 141,326,431,455 11,558 12,227,585.3 7,211,303.0 21,424 658,160,680 14,124,156.6 sem_wait
0.1 5,907,485,407 725 8,148,255.7 1,042.0 1,000 442,887,066 44,916,303.4 waitpid
0.0 1,252,683,205 505,872 2,476.3 1,440.0 1,006 94,581,342 133,009.9 munmap
0.0 907,262,068 353 2,570,147.5 1,227,045.0 1,197 26,263,430 3,108,782.5 pthread_rwlock_wrlock
0.0 708,053,362 172 4,116,589.3 615,554.5 3,112 29,565,907 7,196,056.2 pthread_join
0.0 327,596,329 10,080 32,499.6 10,962.5 1,000 29,220,721 379,953.4 ioctl
0.0 261,805,946 495 528,900.9 2,972.0 1,077 19,958,090 3,072,110.4 fopen
0.0 160,631,905 36,713 4,375.3 3,385.0 1,000 1,692,951 12,061.0 mmap64
0.0 150,219,603 6,263 23,985.2 8,256.0 1,010 2,585,639 128,799.4 pthread_mutex_lock
0.0 126,650,615 25 5,066,024.6 5,065,286.0 5,053,603 5,077,238 7,361.7 nanosleep
0.0 99,487,929 31,988 3,110.2 2,516.0 1,000 75,099 2,795.8 open64
0.0 90,344,763 9,083 9,946.6 4,712.0 1,148 2,648,924 36,587.2 recv
0.0 84,823,390 9,082 9,339.7 5,735.5 1,468 89,916 8,146.6 send
0.0 78,685,390 43,321 1,816.3 1,662.0 1,000 354,334 2,967.5 pthread_cond_signal
0.0 69,793,423 5,751 12,135.9 2,001.0 1,035 19,751,200 420,727.9 open
0.0 66,948,530 15,954 4,196.3 2,557.0 1,010 575,245 10,386.1 write
0.0 50,999,387 10 5,099,938.7 19,477.5 9,808 50,802,125 16,058,116.0 connect
0.0 18,140,344 11,019 1,646.3 1,411.0 1,000 24,064 709.4 epoll_ctl
0.0 18,080,692 280 64,573.9 51,655.5 16,288 578,620 60,626.8 pthread_create
0.0 9,776,017 147 66,503.5 68,572.0 55,588 85,413 5,091.0 sleep
0.0 7,076,518 18 393,139.9 383,949.5 262,109 584,262 85,377.7 posix_spawn
0.0 6,601,831 899 7,343.5 5,539.0 1,010 84,493 9,244.8 fgets
0.0 5,962,720 22 271,032.7 169,725.0 16,478 675,901 237,522.4 pthread_rwlock_rdlock
0.0 3,506,178 342 10,252.0 2,354.5 1,006 207,881 30,027.2 pthread_cond_broadcast
0.0 3,013,330 1,417 2,126.6 1,083.0 1,008 110,583 7,412.5 fclose
0.0 2,975,781 1,319 2,256.1 1,598.0 1,000 22,362 1,984.6 stat
0.0 2,885,075 692 4,169.2 4,026.5 1,238 45,085 4,258.3 fopen64
0.0 2,145,928 345 6,220.1 3,291.0 1,000 51,101 8,060.8 fread
0.0 1,950,425 65 30,006.5 3,106.0 1,201 261,266 71,483.9 futex
0.0 1,877,146 336 5,586.7 4,406.0 1,002 83,435 6,148.2 mmap
0.0 1,741,859 102 17,077.0 4,155.5 1,030 432,266 67,240.1 fwrite
0.0 1,680,806 1,203 1,397.2 1,251.0 1,000 8,322 493.0 fstat
0.0 1,075,803 1 1,075,803.0 1,075,803.0 1,075,803 1,075,803 0.0 fork
0.0 721,566 99 7,288.5 6,229.0 2,560 17,976 3,711.4 pipe2
0.0 595,674 19 31,351.3 5,092.0 4,006 383,239 86,162.0 putc
0.0 248,534 41 6,061.8 4,850.0 1,628 18,035 4,032.6 socket
0.0 183,085 115 1,592.0 1,513.0 1,001 2,876 429.3 sigaction
0.0 167,627 16 10,476.7 2,835.5 1,086 55,140 16,437.5 bind
0.0 115,447 8 14,430.9 6,418.0 3,542 41,638 15,571.8 fputs
0.0 93,879 16 5,867.4 5,035.0 1,640 14,112 3,769.0 lstat
0.0 60,214 6 10,035.7 10,003.0 9,288 10,680 531.1 getc
0.0 49,588 27 1,836.6 1,677.0 1,019 2,939 596.6 dup2
0.0 47,084 37 1,272.5 1,112.0 1,002 3,284 431.2 fcntl
0.0 37,610 24 1,567.1 1,488.5 1,021 2,512 357.1 signal
0.0 35,001 5 7,000.2 7,792.0 3,662 10,502 2,759.1 accept4
0.0 31,541 9 3,504.6 4,424.0 1,078 6,400 2,269.5 fflush
0.0 15,432 4 3,858.0 3,690.5 2,526 5,525 1,477.8 flock
0.0 15,311 11 1,391.9 1,301.0 1,125 1,918 254.0 listen
0.0 14,040 8 1,755.0 1,552.0 1,310 3,235 642.4 pread
0.0 12,841 3 4,280.3 4,425.0 3,921 4,495 313.2 fputs_unlocked
0.0 12,488 5 2,497.6 2,496.0 2,206 2,947 282.0 mprotect
0.0 10,666 1 10,666.0 10,666.0 10,666 10,666 0.0 dup
0.0 6,561 3 2,187.0 1,727.0 1,636 3,198 876.7 flockfile
0.0 6,208 1 6,208.0 6,208.0 6,208 6,208 0.0 kill
0.0 3,788 2 1,894.0 1,894.0 1,355 2,433 762.3 openat64
0.0 2,317 2 1,158.5 1,158.5 1,025 1,292 188.8 pthread_mutex_trylock
[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
-------- --------------- --------- ----------- ----------- -------- ----------- ----------- ------------------------------------------
54.0 18,079,332,597 62,830 287,750.0 8,213.0 2,790 112,775,333 1,983,727.7 cudaMemcpyAsync
21.3 7,151,454,905 1,151,462 6,210.8 4,908.0 775 60,344,468 100,074.1 cudaLaunchKernel
13.9 4,659,698,239 3,031 1,537,346.8 36,322.0 1,646 137,811,508 5,892,401.8 cudaDeviceSynchronize
5.7 1,902,754,251 154,454 12,319.2 10,944.0 7,132 6,919,461 39,439.6 cudaGraphLaunch_v10000
2.4 817,695,167 151,595 5,393.9 4,998.0 606 8,288,395 63,229.0 cuLaunchKernel
0.7 225,761,461 1,943 116,192.2 74,685.0 38,766 1,503,454 195,876.4 cudaGraphInstantiateWithFlags_v11040
0.4 145,677,030 27,893 5,222.7 5,401.0 170 3,577,542 23,514.0 cudaMemsetAsync
0.4 123,078,496 156,852 784.7 749.0 293 28,187 217.2 cudaStreamIsCapturing_v10000
0.2 80,818,259 41,653 1,940.3 1,901.0 1,681 230,930 1,185.3 cudaEventRecord
0.2 70,123,080 11,007 6,370.8 2,991.0 1,576 11,464,127 117,490.1 cudaStreamSynchronize
0.2 54,985,787 222 247,683.7 127,094.5 70,289 2,353,583 356,501.3 cudaFree
0.1 39,808,657 349 114,064.9 107,734.0 9,252 1,028,648 56,280.0 cudaMalloc
0.1 33,850,909 41,671 812.3 782.0 275 186,043 928.6 cudaEventCreateWithFlags
0.1 25,030,442 10 2,503,044.2 2,591,457.0 57,483 4,465,642 1,429,904.6 cuLibraryLoadData
0.1 20,138,251 281 71,666.4 73,047.0 25,875 416,759 45,705.2 cuModuleLoadData
0.1 18,115,827 41,653 434.9 403.0 338 226,830 1,887.5 cudaEventDestroy
0.1 17,924,935 16,808 1,066.5 493.0 261 6,344,359 50,228.8 cuKernelGetFunction
0.0 9,263,417 18,895 490.3 467.0 322 6,477 105.4 cudaStreamGetCaptureInfo_v2_v11030
0.0 7,974,210 1,943 4,104.1 4,022.0 3,214 9,676 584.5 cudaStreamBeginCapture_v10000
0.0 7,518,878 1,943 3,869.7 3,828.0 2,357 7,833 536.7 cudaGraphDestroy_v10000
0.0 3,416,827 128 26,694.0 2,299.0 1,471 1,153,703 140,616.2 cudaStreamCreateWithPriority
0.0 2,744,082 1,943 1,412.3 1,389.0 1,050 7,178 196.6 cudaStreamEndCapture_v10000
0.0 1,570,575 1,943 808.3 739.0 614 2,547 251.2 cudaGraphGetNodes_v10000
0.0 1,322,243 15 88,149.5 6,436.0 3,579 1,170,830 300,044.6 cudaHostAlloc
0.0 280,352 8 35,044.0 26,955.5 12,673 101,212 28,421.5 cudaMemGetInfo
0.0 138,906 810 171.5 140.0 79 1,705 118.0 cuGetProcAddress_v2
0.0 23,009 16 1,438.1 808.5 451 5,531 1,508.2 cuLibraryGetKernel
0.0 8,159 14 582.8 544.5 324 990 193.4 cudaThreadExchangeStreamCaptureMode_v10010
0.0 4,031 1 4,031.0 4,031.0 4,031 4,031 0.0 cudaStreamWaitEvent
0.0 3,969 3 1,323.0 1,051.0 1,031 1,887 488.5 cuInit
0.0 3,693 4 923.3 916.5 75 1,785 960.8 cuModuleGetLoadingMode
0.0 1,064 2 532.0 532.0 356 708 248.9 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
-------- --------------- --------- ----------- ----------- --------- --------- ----------- ----------------------------------------------------------------------------------------------------
30.6 11,421,290,038 118,048 96,751.2 42,337.0 12,320 576,069 124,175.4 void flash::flash_fwd_splitkv_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (int)4, (…
20.4 7,605,306,813 28,807 264,009.0 265,858.0 32,961 765,542 115,223.0 ampere_bf16_s1688gemm_bf16_64x128_sliced1x2_ldg8_f2f_tn
8.8 3,277,208,753 47,634 68,799.8 77,473.0 800 81,121 21,559.5 void at::native::vectorized_elementwise_kernel<(int)4, at::native::FillFunctor<int>, std::array<cha…
5.6 2,083,505,861 1,271 1,639,265.0 1,387,852.0 39,745 4,515,436 1,121,994.0 ampere_bf16_s1688gemm_bf16_128x128_ldg8_f2f_stages_32x1_tn
5.1 1,891,072,505 20,210 93,571.1 20,224.0 1,055 481,762 169,672.7 triton_poi_fused_mul_silu_1
4.3 1,624,497,751 101,584 15,991.7 8,544.0 6,367 81,025 11,832.8 void flash::flash_fwd_splitkv_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (int)4, (…
3.3 1,229,556,187 9,203 133,603.8 42,977.0 7,648 557,317 169,265.9 void cutlass::Kernel2<cutlass_80_tensorop_bf16_s16816gemm_relu_bf16_64x64_32x6_tn_align8>(T1::Param…
2.5 940,467,368 5,865 160,352.5 13,312.0 1,984 1,008,298 288,283.2 void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIterator…
2.2 808,325,696 2,044 395,462.7 496,644.0 10,592 510,980 192,958.7 void cutlass::Kernel2<cutlass_80_wmma_tensorop_bf16_s161616gemm_bf16_16x16_128x2_tn_align8>(T1::Par…
1.9 720,826,362 5,867 122,861.1 9,824.0 5,120 714,183 210,401.9 void at::native::reduce_kernel<(int)512, (int)1, at::native::ReduceOp<float, at::native::ArgMaxOps<…
1.8 666,198,895 287,392 2,318.1 1,920.0 1,536 6,368 968.2 void at::native::elementwise_kernel<(int)128, (int)4, void at::native::gpu_kernel_impl_nocast<at::n…
1.6 609,901,106 6,048 100,843.4 32,161.0 6,912 3,159,614 305,220.1 void flash::flash_fwd_splitkv_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (int)4, (…
1.5 576,753,139 13,496 42,735.1 42,624.0 26,016 102,081 3,914.6 ampere_bf16_s1688gemm_bf16_128x64_sliced1x2_ldg8_relu_f2f_tn
1.3 487,869,104 13,020 37,470.7 37,440.0 36,640 42,816 321.1 ampere_bf16_s1688gemm_bf16_64x64_sliced1x4_ldg8_f2f_tn
1.2 431,150,928 22,086 19,521.5 3,489.0 1,344 75,104 27,792.8 triton_poi_fused_cat_3
0.9 347,479,864 341 1,019,002.5 598,630.0 373,475 2,788,687 741,262.9 ampere_bf16_s16816gemm_bf16_128x64_ldg8_f2f_tn
0.8 316,815,668 1,904 166,394.8 154,193.5 40,352 1,291,207 149,498.4 ampere_bf16_s1688gemm_bf16_128x64_sliced1x2_ldg8_f2f_tn
0.7 264,631,581 521 507,930.1 507,844.0 506,244 519,973 763.9 void cutlass::Kernel2<cutlass_80_wmma_tensorop_bf16_s161616gemm_bf16_16x16_128x1_tn_align8>(T1::Par…
0.7 258,705,730 610 424,107.8 487,972.0 6,976 500,003 159,920.1 std::enable_if<!T7, void>::type internal::gemvx::kernel<int, int, __nv_bfloat16, __nv_bfloat16, __n…
0.7 248,913,221 164,164 1,516.2 1,280.0 1,023 13,249 475.7 void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0…
0.6 206,205,114 57,848 3,564.6 3,584.0 3,295 3,936 112.4 void flash::flash_fwd_splitkv_combine_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (…
0.5 203,900,076 143,696 1,419.0 1,344.0 1,183 2,208 221.7 void at::native::elementwise_kernel<(int)128, (int)2, void at::native::gpu_kernel_impl_nocast<at::n…
0.5 189,670,922 16,968 11,178.2 12,256.0 1,536 111,105 5,147.2 triton_red_fused__to_copy_add_mean_mul_pow_rsqrt_2
0.5 173,673,906 22,086 7,863.5 2,368.0 832 25,696 9,575.0 triton_poi_fused_view_5
0.5 170,442,702 61,516 2,770.7 2,432.0 1,247 17,088 1,351.4 void vllm::merge_attn_states_kernel<__nv_bfloat16, (unsigned int)128>(T1 *, float *, const T1 *, co…
0.3 95,480,145 22,086 4,323.1 1,376.0 1,215 15,104 5,013.1 triton_poi_fused_cat_4
0.2 88,249,892 16,968 5,201.0 5,473.0 1,535 80,096 3,526.8 triton_red_fused__to_copy_add_mean_mul_pow_rsqrt_0
0.2 58,167,224 15,232 3,818.8 3,840.0 3,711 4,032 31.4 void flash::flash_fwd_splitkv_combine_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (…
0.1 45,137,635 14,420 3,130.2 3,167.0 3,008 3,457 59.7 void flash::flash_fwd_splitkv_combine_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (…
0.1 43,394,155 14,084 3,081.1 3,072.0 3,008 3,200 19.7 void flash::flash_fwd_splitkv_combine_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (…
0.1 39,138,907 8 4,892,363.4 4,849,279.0 4,795,198 5,088,513 110,842.2 void at_cuda_detail::cub::DeviceSegmentedRadixSortKernel<at_cuda_detail::cub::DeviceRadixSortPolicy…
0.1 22,694,961 784 28,947.7 12,575.5 11,744 62,528 20,606.8 ampere_bf16_s16816gemm_bf16_64x64_ldg8_f2f_stages_64x5_tn
0.1 20,952,447 5,999 3,492.7 3,104.0 2,751 7,392 961.1 void at::native::index_elementwise_kernel<(int)128, (int)4, void at::native::gpu_index_kernel<void …
0.1 20,383,074 4 5,095,768.5 5,085,968.5 4,915,359 5,295,778 195,206.9 void at_cuda_detail::cub::DeviceSegmentedRadixSortKernel<at_cuda_detail::cub::DeviceRadixSortPolicy…
0.0 15,859,055 818 19,387.6 3,136.0 1,600 74,881 27,973.6 triton_poi_fused_cat_1
0.0 14,288,503 28 510,303.7 511,683.0 469,923 513,059 7,932.0 void at::native::vectorized_elementwise_kernel<(int)4, at::native::FillFunctor<signed char>, std::a…
0.0 9,813,089 4 2,453,272.3 2,468,672.5 2,391,504 2,484,240 42,132.0 void at::native::<unnamed>::cunn_SoftMaxForward<(int)4, float, float, float, at::native::<unnamed>:…
0.0 9,653,448 448 21,547.9 21,345.0 21,120 24,928 817.3 ampere_bf16_s16816gemm_bf16_128x64_ldg8_f2f_stages_32x6_tn
0.0 9,408,780 5,863 1,604.8 1,376.0 1,120 2,752 455.9 void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIterator…
0.0 8,489,112 224 37,897.8 37,856.0 36,545 39,328 536.2 void cutlass::Kernel2<cutlass_80_tensorop_bf16_s16816gemm_relu_bf16_64x128_32x6_tn_align8>(T1::Para…
0.0 8,311,916 28 296,854.1 294,593.5 293,505 332,482 7,194.4 ampere_bf16_s1688gemm_bf16_128x128_ldg8_relu_f2f_stages_32x1_tn
0.0 7,845,574 9,023 869.5 864.0 767 1,281 77.2 void at::native::vectorized_elementwise_kernel<(int)2, at::native::FillFunctor<long>, std::array<ch…
0.0 7,775,377 2 3,887,688.5 3,887,688.5 3,705,239 4,070,138 258,022.6 void at::native::_scatter_gather_elementwise_kernel<(int)128, (int)8, void at::native::_cuda_scatte…
0.0 7,471,240 5,865 1,273.9 1,120.0 991 2,080 282.3 void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIterator…
0.0 7,214,254 336 21,471.0 21,408.0 21,056 22,625 299.8 ampere_bf16_s16816gemm_bf16_128x64_ldg8_relu_f2f_stages_64x3_tn
0.0 6,324,707 818 7,731.9 2,368.0 863 24,832 9,334.7 triton_poi_fused_view_3
0.0 6,169,925 476 12,962.0 12,864.0 11,776 14,304 602.5 ampere_bf16_s16816gemm_bf16_64x64_ldg8_relu_f2f_stages_64x5_tn
0.0 5,903,909 4 1,475,977.3 1,475,449.0 1,472,585 1,480,426 3,980.7 void at::native::vectorized_elementwise_kernel<(int)4, at::native::<unnamed>::masked_fill_kernel(at…
0.0 5,501,036 5,863 938.3 928.0 895 1,312 71.9 void at::native::unrolled_elementwise_kernel<at::native::CUDAFunctorOnSelf_add<int>, std::array<cha…
0.0 4,936,334 28 176,297.6 176,817.5 174,209 178,978 1,446.6 ampere_bf16_s1688gemm_bf16_64x128_sliced1x2_ldg8_relu_f2f_tn
0.0 4,754,998 5,432 875.4 864.0 800 1,217 36.3 void at::native::unrolled_elementwise_kernel<at::native::FillFunctor<int>, std::array<char *, (unsi…
0.0 3,995,930 2 1,997,965.0 1,997,965.0 1,996,108 1,999,822 2,626.2 void at::native::vectorized_elementwise_kernel<(int)4, at::native::BinaryFunctor<float, float, floa…
0.0 3,598,526 56 64,259.4 64,320.5 63,104 65,313 559.8 void cutlass::Kernel2<cutlass_80_wmma_tensorop_bf16_s161616gemm_bf16_32x32_64x1_tn_align8>(T1::Para…
0.0 3,541,818 818 4,329.9 1,376.0 1,215 14,815 5,022.4 triton_poi_fused_cat_2
0.0 3,434,102 4 858,525.5 858,069.5 855,685 862,278 2,939.8 void at::native::elementwise_kernel<(int)128, (int)4, void at::native::gpu_kernel_impl_nocast<at::n…
0.0 3,192,725 2 1,596,362.5 1,596,362.5 1,563,050 1,629,675 47,111.0 void at::native::tensor_kernel_scan_innermost_dim<float, std::plus<float>>(T1 *, const T1 *, unsign…
0.0 2,897,906 1,512 1,916.6 1,824.0 1,312 2,976 438.1 void cublasLt::splitKreduce_kernel<(int)32, (int)16, int, __nv_bfloat16, __nv_bfloat16, float, (boo…
0.0 2,593,403 606 4,279.5 4,384.0 1,984 35,904 1,445.1 triton_red_fused__to_copy_add_embedding_mean_mul_pow_rsqrt_0
0.0 2,582,288 2 1,291,144.0 1,291,144.0 1,290,536 1,291,752 859.8 at::native::<unnamed>::fill_reverse_indices_kernel(long *, int, at::cuda::detail::IntDivider<unsign…
0.0 2,580,625 2 1,290,312.5 1,290,312.5 1,288,393 1,292,232 2,714.6 void at::native::elementwise_kernel<(int)128, (int)2, void at::native::gpu_kernel_impl_nocast<at::n…
0.0 2,421,451 112 21,620.1 21,552.0 9,376 34,400 12,006.5 void cutlass::Kernel2<cutlass_80_wmma_tensorop_bf16_s161616gemm_bf16_32x32_128x2_tn_align8>(T1::Par…
0.0 1,377,256 2 688,628.0 688,628.0 682,820 694,436 8,213.8 void at::native::<unnamed>::distribution_elementwise_grid_stride_kernel<float, (int)4, void at::nat…
0.0 1,128,024 1,252 901.0 896.0 800 1,280 45.2 void at::native::vectorized_elementwise_kernel<(int)2, at::native::FillFunctor<int>, std::array<cha…
0.0 957,446 28 34,194.5 34,768.5 17,983 35,232 3,184.5 std::enable_if<!T7, void>::type internal::gemvx::kernel<int, int, __nv_bfloat16, float, float, floa…
0.0 670,018 731 916.6 928.0 863 1,024 22.0 void at::native::unrolled_elementwise_kernel<at::native::FillFunctor<long>, std::array<char *, (uns…
0.0 296,898 168 1,767.3 1,760.0 1,536 2,080 121.8 void cublasLt::splitKreduce_kernel<(int)32, (int)16, int, __nv_bfloat16, __nv_bfloat16, float, (boo…
0.0 157,249 1 157,249.0 157,249.0 157,249 157,249 0.0 void at::native::<unnamed>::CatArrayBatchedCopy_aligned16_contig<at::native::<unnamed>::OpaqueType<…
0.0 90,491 86 1,052.2 927.5 895 11,488 1,139.9 void at::native::vectorized_elementwise_kernel<(int)4, at::native::FillFunctor<c10::BFloat16>, std:…
0.0 78,785 1 78,785.0 78,785.0 78,785 78,785 0.0 void at::native::vectorized_elementwise_kernel<(int)4, at::native::bfloat16_copy_kernel_cuda(at::Te…
0.0 43,232 1 43,232.0 43,232.0 43,232 43,232 0.0 void at::native::vectorized_elementwise_kernel<(int)4, at::native::sin_kernel_cuda(at::TensorIterat…
0.0 36,737 28 1,312.0 1,312.0 1,280 1,344 17.4 void cublasLt::splitKreduce_kernel<(int)32, (int)16, int, float, __nv_bfloat16, float, (bool)0, __n…
0.0 26,432 1 26,432.0 26,432.0 26,432 26,432 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 11,713 11 1,064.8 864.0 800 1,536 305.4 void at::native::vectorized_elementwise_kernel<(int)4, at::native::FillFunctor<float>, std::array<c…
0.0 10,624 2 5,312.0 5,312.0 5,024 5,600 407.3 void at::native::_scatter_gather_elementwise_kernel<(int)128, (int)8, void at::native::_cuda_scatte…
0.0 8,639 2 4,319.5 4,319.5 4,128 4,511 270.8 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 3,489 2 1,744.5 1,744.5 1,696 1,793 68.6 void at::native::vectorized_elementwise_kernel<(int)2, at::native::CUDAFunctorOnOther_add<long>, st…
0.0 3,103 2 1,551.5 1,551.5 1,503 1,600 68.6 void at::native::vectorized_elementwise_kernel<(int)2, at::native::<unnamed>::where_kernel_impl(at:…
0.0 2,976 2 1,488.0 1,488.0 1,376 1,600 158.4 void at::native::vectorized_elementwise_kernel<(int)4, void at::native::compare_scalar_kernel<float…
0.0 2,975 2 1,487.5 1,487.5 991 1,984 702.2 void <unnamed>::elementwise_kernel_with_index<int, at::native::arange_cuda_out(const c10::Scalar &,…
0.0 2,944 2 1,472.0 1,472.0 1,344 1,600 181.0 void at::native::vectorized_elementwise_kernel<(int)4, at::native::CUDAFunctorOnOther_add<float>, s…
0.0 2,400 1 2,400.0 2,400.0 2,400 2,400 0.0 void at::native::elementwise_kernel<(int)128, (int)4, void at::native::gpu_kernel_impl<at::native::…
0.0 1,185 1 1,185.0 1,185.0 1,185 1,185 0.0 void at::native::vectorized_elementwise_kernel<(int)4, at::native::reciprocal_kernel_cuda(at::Tenso…
0.0 1,025 1 1,025.0 1,025.0 1,025 1,025 0.0 void at::native::vectorized_elementwise_kernel<(int)4, at::native::AUnaryFunctor<float, float, floa…
0.0 1,025 1 1,025.0 1,025.0 1,025 1,025 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
-------- --------------- ------ -------- -------- -------- ----------- ----------- ------------------------------
93.8 627,226,731 42,463 14,771.1 352.0 320 112,333,155 587,539.7 [CUDA memcpy Host-to-Device]
2.8 18,735,373 14,448 1,296.7 928.0 895 1,362,505 22,615.1 [CUDA memcpy Device-to-Device]
2.4 16,204,705 24,393 664.3 768.0 320 8,224 282.8 [CUDA memset]
1.0 6,719,471 5,919 1,135.2 1,120.0 863 1,920 102.9 [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
---------- ------ -------- -------- -------- -------- ----------- ------------------------------
4,194.770 42,463 0.099 0.000 0.000 466.747 2.582 [CUDA memcpy Host-to-Device]
2,533.618 14,448 0.175 0.003 0.000 622.330 10.354 [CUDA memcpy Device-to-Device]
17.613 24,393 0.001 0.001 0.000 0.006 0.000 [CUDA memset]
4.192 5,919 0.001 0.000 0.000 0.004 0.001 [CUDA memcpy Device-to-Host]
Generated:
/data/cy/kv_cache_vs_util/std_traverse_bs/traverse_bs_util_std.nsys-rep
/data/cy/kv_cache_vs_util/std_traverse_bs/traverse_bs_util_std.sqlite
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