From a546830c1bc42f03961687ca4e79d110f96d3b9c Mon Sep 17 00:00:00 2001 From: github-action-benchmark Date: Sun, 22 Dec 2024 02:39:47 +0000 Subject: [PATCH] add smaller_is_better (customSmallerIsBetter) benchmark result for dabca025e458f83e9de82f68aef29b3260214c16 --- dev/bench/data.js | 48 ++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 47 insertions(+), 1 deletion(-) diff --git a/dev/bench/data.js b/dev/bench/data.js index e017075..3780b86 100644 --- a/dev/bench/data.js +++ b/dev/bench/data.js @@ -1,5 +1,5 @@ window.BENCHMARK_DATA = { - "lastUpdate": 1734834563132, + "lastUpdate": 1734835186987, "repoUrl": "https://github.com/neuralmagic/nm-vllm-ent", "entries": { "smaller_is_better": [ @@ -2164,6 +2164,52 @@ window.BENCHMARK_DATA = { "extra": "{\"description\": \"VLLM Serving - Dense\\nmodel - meta-llama/Meta-Llama-3-8B-Instruct\\nmax-model-len - 4096\\nsparsity - None\\nbenchmark_serving {\\n \\\"nr-qps-pair_\\\": \\\"300,1\\\",\\n \\\"dataset\\\": \\\"sharegpt\\\"\\n}\", \"benchmarking_context\": {\"vllm_version\": \"0.6.3.0.20241222\", \"python_version\": \"3.10.12\", \"torch_version\": \"2.4.0+cu121\", \"torch_cuda_version\": \"12.1\", \"cuda_devices\": \"[_CudaDeviceProperties(name='NVIDIA L4', major=8, minor=9, total_memory=22593MB, multi_processor_count=58)]\", \"cuda_device_names\": [\"NVIDIA L4\"]}, \"gpu_description\": \"NVIDIA L4 x 1\", \"script_name\": \"benchmark_serving.py\", \"script_args\": {\"description\": \"VLLM Serving - Dense\\nmodel - meta-llama/Meta-Llama-3-8B-Instruct\\nmax-model-len - 4096\\nsparsity - None\\nbenchmark_serving {\\n \\\"nr-qps-pair_\\\": \\\"300,1\\\",\\n \\\"dataset\\\": \\\"sharegpt\\\"\\n}\", \"backend\": \"vllm\", \"version\": \"N/A\", \"base_url\": null, \"host\": \"127.0.0.1\", \"port\": 9000, \"endpoint\": \"/generate\", \"dataset\": \"sharegpt\", \"num_input_tokens\": null, \"num_output_tokens\": null, \"model\": \"meta-llama/Meta-Llama-3-8B-Instruct\", \"tokenizer\": \"meta-llama/Meta-Llama-3-8B-Instruct\", \"best_of\": 1, \"use_beam_search\": false, \"log_model_io\": false, \"seed\": 0, \"trust_remote_code\": false, \"disable_tqdm\": false, \"save_directory\": \"benchmark-results\", \"num_prompts_\": null, \"request_rate_\": null, \"nr_qps_pair_\": [300, \"1.0\"], \"server_tensor_parallel_size\": 1, \"server_args\": \"{'model': 'meta-llama/Meta-Llama-3-8B-Instruct', 'tokenizer': 'meta-llama/Meta-Llama-3-8B-Instruct', 'max-model-len': 4096, 'host': '127.0.0.1', 'port': 9000, 'tensor-parallel-size': 1, 'disable-log-requests': ''}\"}, \"date\": \"2024-12-22 02:28:09 UTC\", \"model\": \"meta-llama/Meta-Llama-3-8B-Instruct\", \"dataset\": \"sharegpt\"}" } ] + }, + { + "commit": { + "author": { + "name": "Domenic Barbuzzi", + "username": "dbarbuzzi", + "email": "domenic@neuralmagic.com" + }, + "committer": { + "name": "GitHub", + "username": "web-flow", + "email": "noreply@github.com" + }, + "id": "dabca025e458f83e9de82f68aef29b3260214c16", + "message": "Add code coverage support (#169)\n\nThis PR restores code coverage support via opt-in flag (i.e., disabled\nby default).\n\nWhen the flag is set, the script that manages the commands to run will\ninclude coverage-related flags to generate data. There are also\nsteps/scripts that are added/modified to handle this data (upload to the\nrun as an artifact, write the results to the job summary).", + "timestamp": "2024-12-19T16:37:19Z", + "url": "https://github.com/neuralmagic/nm-vllm-ent/commit/dabca025e458f83e9de82f68aef29b3260214c16" + }, + "date": 1734835185627, + "tool": "customSmallerIsBetter", + "benches": [ + { + "name": "{\"name\": \"mean_ttft_ms\", \"description\": \"VLLM Serving - Dense\\nmodel - meta-llama/Meta-Llama-3-70B-Instruct\\nmax-model-len - 4096\\nsparsity - None\\nbenchmark_serving {\\n \\\"nr-qps-pair_\\\": \\\"300,1\\\",\\n \\\"dataset\\\": \\\"sharegpt\\\"\\n}\", \"gpu_description\": \"NVIDIA A100-SXM4-80GB x 4\", \"python_version\": \"3.10.12\", \"torch_version\": \"2.4.0+cu121\"}", + "value": 166.393755680571, + "unit": "ms", + "extra": "{\"description\": \"VLLM Serving - Dense\\nmodel - meta-llama/Meta-Llama-3-70B-Instruct\\nmax-model-len - 4096\\nsparsity - None\\nbenchmark_serving {\\n \\\"nr-qps-pair_\\\": \\\"300,1\\\",\\n \\\"dataset\\\": \\\"sharegpt\\\"\\n}\", \"benchmarking_context\": {\"vllm_version\": \"0.6.3.0.20241222\", \"python_version\": \"3.10.12\", \"torch_version\": \"2.4.0+cu121\", \"torch_cuda_version\": \"12.1\", \"cuda_devices\": \"[_CudaDeviceProperties(name='NVIDIA A100-SXM4-80GB', major=8, minor=0, total_memory=81049MB, multi_processor_count=108), _CudaDeviceProperties(name='NVIDIA A100-SXM4-80GB', major=8, minor=0, total_memory=81049MB, multi_processor_count=108), _CudaDeviceProperties(name='NVIDIA A100-SXM4-80GB', major=8, minor=0, total_memory=81049MB, multi_processor_count=108), _CudaDeviceProperties(name='NVIDIA A100-SXM4-80GB', major=8, minor=0, total_memory=81049MB, multi_processor_count=108)]\", \"cuda_device_names\": [\"NVIDIA A100-SXM4-80GB\", \"NVIDIA A100-SXM4-80GB\", \"NVIDIA A100-SXM4-80GB\", \"NVIDIA A100-SXM4-80GB\"]}, \"gpu_description\": \"NVIDIA A100-SXM4-80GB x 4\", \"script_name\": \"benchmark_serving.py\", \"script_args\": {\"description\": \"VLLM Serving - 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Dense\\nmodel - meta-llama/Meta-Llama-3-70B-Instruct\\nmax-model-len - 4096\\nsparsity - None\\nbenchmark_serving {\\n \\\"nr-qps-pair_\\\": \\\"300,1\\\",\\n \\\"dataset\\\": \\\"sharegpt\\\"\\n}\", \"gpu_description\": \"NVIDIA A100-SXM4-80GB x 4\", \"python_version\": \"3.10.12\", \"torch_version\": \"2.4.0+cu121\"}", + "value": 39.70706452933001, + "unit": "ms", + "extra": "{\"description\": \"VLLM Serving - Dense\\nmodel - meta-llama/Meta-Llama-3-70B-Instruct\\nmax-model-len - 4096\\nsparsity - None\\nbenchmark_serving {\\n \\\"nr-qps-pair_\\\": \\\"300,1\\\",\\n \\\"dataset\\\": \\\"sharegpt\\\"\\n}\", \"benchmarking_context\": {\"vllm_version\": \"0.6.3.0.20241222\", \"python_version\": \"3.10.12\", \"torch_version\": \"2.4.0+cu121\", \"torch_cuda_version\": \"12.1\", \"cuda_devices\": \"[_CudaDeviceProperties(name='NVIDIA A100-SXM4-80GB', major=8, minor=0, total_memory=81049MB, multi_processor_count=108), _CudaDeviceProperties(name='NVIDIA A100-SXM4-80GB', major=8, minor=0, total_memory=81049MB, multi_processor_count=108), _CudaDeviceProperties(name='NVIDIA A100-SXM4-80GB', major=8, minor=0, total_memory=81049MB, multi_processor_count=108), _CudaDeviceProperties(name='NVIDIA A100-SXM4-80GB', major=8, minor=0, total_memory=81049MB, multi_processor_count=108)]\", \"cuda_device_names\": [\"NVIDIA A100-SXM4-80GB\", \"NVIDIA A100-SXM4-80GB\", \"NVIDIA A100-SXM4-80GB\", \"NVIDIA A100-SXM4-80GB\"]}, \"gpu_description\": \"NVIDIA A100-SXM4-80GB x 4\", \"script_name\": \"benchmark_serving.py\", \"script_args\": {\"description\": \"VLLM Serving - 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