diff --git a/dev/bench/data.js b/dev/bench/data.js index 4b80185..854c5aa 100644 --- a/dev/bench/data.js +++ b/dev/bench/data.js @@ -1,54 +1,8 @@ window.BENCHMARK_DATA = { - "lastUpdate": 1734920927058, + "lastUpdate": 1734921599195, "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": "271bafa0bc4d83cbdc0841e2a50f046552741872", - "message": "Use 4x A100s (not 4x H100s) during remote push (#165)\n\nThis PR updates one of the remote push jobs to use a `k8s-a100-quad`\ninstead of a `k8s-h100-quad`, as the latter would tie up all of our\nH100s (as well as delay the job until they are all available).", - "timestamp": "2024-12-11T21:01:46Z", - "url": "https://github.com/neuralmagic/nm-vllm-ent/commit/271bafa0bc4d83cbdc0841e2a50f046552741872" - 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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": 1734921597766, + "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": 172.86732893437147, + "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\": \"0.6.3.0.20241223\", \"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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