From 908cbb369a9c81fe819f3bed9c311bfeeda7ba14 Mon Sep 17 00:00:00 2001 From: github-action-benchmark Date: Wed, 1 Jan 2025 04:07:35 +0000 Subject: [PATCH] add smaller_is_better (customSmallerIsBetter) benchmark result for b5d97744548e7e7e155d3625edaa2927864c62e5 --- dev/bench/data.js | 94 +++++++++++++++++++++++------------------------ 1 file changed, 47 insertions(+), 47 deletions(-) diff --git a/dev/bench/data.js b/dev/bench/data.js index 46b9939..3c3558f 100644 --- a/dev/bench/data.js +++ b/dev/bench/data.js @@ -1,54 +1,8 @@ window.BENCHMARK_DATA = { - "lastUpdate": 1735700146044, + "lastUpdate": 1735704455565, "repoUrl": "https://github.com/neuralmagic/nm-vllm-ent", "entries": { "smaller_is_better": [ - { - "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": 1734750029757, - "tool": "customSmallerIsBetter", - "benches": [ - { - "name": "{\"name\": \"mean_ttft_ms\", \"description\": \"VLLM Serving - Dense\\nmodel - mistralai/Mixtral-8x7B-Instruct-v0.1\\nmax-model-len - 4096\\nsparsity - None\\nbenchmark_serving {\\n \\\"nr-qps-pair_\\\": \\\"300,1\\\",\\n \\\"dataset\\\": \\\"sharegpt\\\"\\n}\", \"gpu_description\": \"NVIDIA H100 80GB HBM3 x 4\", \"python_version\": \"3.10.12\", \"torch_version\": \"2.4.0+cu121\"}", - "value": 605.4038932795326, - "unit": "ms", - "extra": "{\"description\": \"VLLM Serving - Dense\\nmodel - mistralai/Mixtral-8x7B-Instruct-v0.1\\nmax-model-len - 4096\\nsparsity - None\\nbenchmark_serving {\\n \\\"nr-qps-pair_\\\": \\\"300,1\\\",\\n \\\"dataset\\\": \\\"sharegpt\\\"\\n}\", \"benchmarking_context\": {\"vllm_version\": \"0.6.3.0.20241221\", \"python_version\": \"3.10.12\", \"torch_version\": \"2.4.0+cu121\", \"torch_cuda_version\": \"12.1\", \"cuda_devices\": \"[_CudaDeviceProperties(name='NVIDIA H100 80GB HBM3', major=9, minor=0, total_memory=80994MB, multi_processor_count=132), _CudaDeviceProperties(name='NVIDIA H100 80GB HBM3', major=9, minor=0, total_memory=80994MB, multi_processor_count=132), _CudaDeviceProperties(name='NVIDIA H100 80GB HBM3', major=9, minor=0, total_memory=80994MB, multi_processor_count=132), _CudaDeviceProperties(name='NVIDIA H100 80GB HBM3', major=9, minor=0, total_memory=80994MB, multi_processor_count=132)]\", \"cuda_device_names\": [\"NVIDIA H100 80GB HBM3\", \"NVIDIA H100 80GB HBM3\", \"NVIDIA H100 80GB HBM3\", \"NVIDIA H100 80GB HBM3\"]}, \"gpu_description\": \"NVIDIA H100 80GB HBM3 x 4\", \"script_name\": \"benchmark_serving.py\", \"script_args\": {\"description\": \"VLLM Serving - 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