| 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] Capturing CUDA graph shapes: 6%|▌ | 4/67 [00:00<00:01, 33.78it/s] Capturing CUDA graph shapes: 12%|█▏ | 8/67 [00:00<00:01, 34.64it/s] Capturing CUDA graph shapes: 18%|█▊ | 12/67 [00:00<00:01, 34.83it/s] Capturing CUDA graph shapes: 24%|██▍ | 16/67 [00:00<00:01, 35.33it/s] Capturing CUDA graph shapes: 30%|██▉ | 20/67 [00:00<00:01, 35.32it/s] Capturing CUDA graph shapes: 36%|███▌ | 24/67 [00:00<00:01, 34.78it/s] Capturing CUDA graph shapes: 42%|████▏ | 28/67 [00:00<00:01, 34.43it/s] Capturing CUDA graph shapes: 48%|████▊ | 32/67 [00:00<00:01, 33.41it/s] Capturing CUDA graph shapes: 54%|█████▎ | 36/67 [00:01<00:00, 32.93it/s] Capturing CUDA graph shapes: 60%|█████▉ | 40/67 [00:01<00:00, 33.79it/s] 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 --- | |
| Adding requests: 0%| | 0/1 [00:00<?, ?it/s] 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 --- | |
| Adding requests: 0%| | 0/2 [00:00<?, ?it/s] 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 --- | |
| Adding requests: 0%| | 0/4 [00:00<?, ?it/s] 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 --- | |
| Adding requests: 0%| | 0/8 [00:00<?, ?it/s] 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 --- | |
| Adding requests: 0%| | 0/16 [00:00<?, ?it/s] 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 --- | |
| Adding requests: 0%| | 0/32 [00:00<?, ?it/s] 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 --- | |
| Adding requests: 0%| | 0/64 [00:00<?, ?it/s] 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 --- | |
| Adding requests: 0%| | 0/512 [00:00<?, ?it/s] 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 --- | |
| Adding requests: 0%| | 0/1024 [00:00<?, ?it/s] 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 | |