From ccf76df58457d0b9161db43b1462f5588882958d Mon Sep 17 00:00:00 2001 From: github-action-benchmark Date: Thu, 5 Sep 2024 02:21:16 +0000 Subject: [PATCH] add smaller_is_better (customSmallerIsBetter) benchmark result for ea0fbbd5bd1581d4d71ce3e8c151db7c792d3bdd --- 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 8699114..787fbba 100644 --- a/dev/bench/data.js +++ b/dev/bench/data.js @@ -1,54 +1,8 @@ window.BENCHMARK_DATA = { - "lastUpdate": 1725502554384, + "lastUpdate": 1725502875984, "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": "2efcd90ff72f4ffe8637f118ad2844d9e44bf789", - "message": "Extended server benchmark model list (#40)\n\nThis PR updates the benchmark configs to include some a large model that\r\nrun on the 4x H100 runner.\r\n\r\nTo accomplish this, the various `benchmark_` inputs to `build-test` are\r\nconsolidated into the JSON-based `benchmark_configs` input (which\r\naccepts a list of objects containing keys: `label`, `config_file`,\r\n`timeout`).\r\n\r\nThis allows the existing benchmarking of ‘small’ models to continue\r\nrunning on the runners they already are, while allowing a new config\r\nwith ‘large’ models to run specifically on the 4x H100 machine.\r\n\r\nAdditionally, the config now supports an optionally-present property to\r\ndefine the server startup timeout, which is set on the large model\r\nconfig (60 min). This will override the default (15 min) if present. In\r\nthe course of adding this support, I fixed a handful of incorrect type\r\nhinting about the config object (as it tripped me up when I tried to use\r\nit as the advertised type, which didn’t work).", - "timestamp": "2024-08-16T15:16:47Z", - "url": "https://github.com/neuralmagic/nm-vllm-ent/commit/2efcd90ff72f4ffe8637f118ad2844d9e44bf789" - }, - "date": 1724035833059, - "tool": "customSmallerIsBetter", - "benches": [ - { - "name": "{\"name\": \"mean_ttft_ms\", \"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}\", \"gpu_description\": \"NVIDIA H100 80GB HBM3 x 1\", \"vllm_version\": \"0.5.3.0\", \"python_version\": \"3.10.12 (main, Jun 7 2023, 13:43:11) [GCC 11.3.0]\", \"torch_version\": \"2.3.1+cu121\"}", - "value": 38.38384596630931, - "unit": "ms", - "extra": "{\n \"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}\",\n \"benchmarking_context\": {\n \"vllm_version\": \"0.5.3.0\",\n \"python_version\": \"3.10.12 (main, Jun 7 2023, 13:43:11) [GCC 11.3.0]\",\n \"torch_version\": \"2.3.1+cu121\",\n \"torch_cuda_version\": \"12.1\",\n \"cuda_devices\": \"[_CudaDeviceProperties(name='NVIDIA H100 80GB HBM3', major=9, minor=0, total_memory=81116MB, multi_processor_count=132)]\",\n \"cuda_device_names\": [\n \"NVIDIA H100 80GB HBM3\"\n ]\n },\n \"gpu_description\": \"NVIDIA H100 80GB HBM3 x 1\",\n \"script_name\": \"benchmark_serving.py\",\n \"script_args\": {\n \"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}\",\n \"backend\": \"vllm\",\n \"version\": \"N/A\",\n \"base_url\": null,\n \"host\": \"127.0.0.1\",\n \"port\": 9000,\n \"endpoint\": \"/generate\",\n \"dataset\": \"sharegpt\",\n \"num_input_tokens\": null,\n \"num_output_tokens\": null,\n \"model\": \"meta-llama/Meta-Llama-3-8B-Instruct\",\n \"tokenizer\": \"meta-llama/Meta-Llama-3-8B-Instruct\",\n \"best_of\": 1,\n \"use_beam_search\": false,\n \"log_model_io\": false,\n \"seed\": 0,\n \"trust_remote_code\": false,\n \"disable_tqdm\": false,\n \"save_directory\": \"benchmark-results\",\n \"num_prompts_\": null,\n \"request_rate_\": null,\n \"nr_qps_pair_\": [\n 300,\n \"1.0\"\n ],\n \"server_tensor_parallel_size\": 1,\n \"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': ''}\"\n },\n \"date\": \"2024-08-19 02:49:20 UTC\",\n \"model\": \"meta-llama/Meta-Llama-3-8B-Instruct\",\n \"dataset\": \"sharegpt\"\n}" - }, - { - "name": "{\"name\": \"mean_tpot_ms\", \"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}\", \"gpu_description\": \"NVIDIA H100 80GB HBM3 x 1\", \"vllm_version\": \"0.5.3.0\", \"python_version\": \"3.10.12 (main, Jun 7 2023, 13:43:11) [GCC 11.3.0]\", \"torch_version\": \"2.3.1+cu121\"}", - "value": 12.523310634132399, - "unit": "ms", - "extra": "{\n \"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}\",\n \"benchmarking_context\": {\n \"vllm_version\": \"0.5.3.0\",\n \"python_version\": \"3.10.12 (main, Jun 7 2023, 13:43:11) [GCC 11.3.0]\",\n \"torch_version\": \"2.3.1+cu121\",\n \"torch_cuda_version\": \"12.1\",\n \"cuda_devices\": \"[_CudaDeviceProperties(name='NVIDIA H100 80GB HBM3', major=9, minor=0, total_memory=81116MB, multi_processor_count=132)]\",\n \"cuda_device_names\": [\n \"NVIDIA H100 80GB HBM3\"\n ]\n },\n \"gpu_description\": \"NVIDIA H100 80GB HBM3 x 1\",\n \"script_name\": \"benchmark_serving.py\",\n \"script_args\": {\n \"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}\",\n \"backend\": \"vllm\",\n \"version\": \"N/A\",\n \"base_url\": null,\n \"host\": \"127.0.0.1\",\n \"port\": 9000,\n \"endpoint\": \"/generate\",\n \"dataset\": \"sharegpt\",\n \"num_input_tokens\": null,\n \"num_output_tokens\": null,\n \"model\": \"meta-llama/Meta-Llama-3-8B-Instruct\",\n \"tokenizer\": \"meta-llama/Meta-Llama-3-8B-Instruct\",\n \"best_of\": 1,\n \"use_beam_search\": false,\n \"log_model_io\": false,\n \"seed\": 0,\n \"trust_remote_code\": false,\n \"disable_tqdm\": false,\n \"save_directory\": \"benchmark-results\",\n \"num_prompts_\": null,\n \"request_rate_\": null,\n \"nr_qps_pair_\": [\n 300,\n \"1.0\"\n ],\n \"server_tensor_parallel_size\": 1,\n \"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': ''}\"\n },\n \"date\": \"2024-08-19 02:49:20 UTC\",\n \"model\": \"meta-llama/Meta-Llama-3-8B-Instruct\",\n \"dataset\": \"sharegpt\"\n}" - }, - { - "name": "{\"name\": \"mean_ttft_ms\", \"description\": \"VLLM Serving - Dense\\nmodel - facebook/opt-350m\\nmax-model-len - 2048\\nsparsity - None\\nbenchmark_serving {\\n \\\"nr-qps-pair_\\\": \\\"300,1\\\",\\n \\\"dataset\\\": \\\"sharegpt\\\"\\n}\", \"gpu_description\": \"NVIDIA H100 80GB HBM3 x 1\", \"vllm_version\": \"0.5.3.0\", \"python_version\": \"3.10.12 (main, Jun 7 2023, 13:43:11) [GCC 11.3.0]\", \"torch_version\": \"2.3.1+cu121\"}", - "value": 37.30297331698239, - "unit": "ms", - "extra": "{\n \"description\": \"VLLM Serving - Dense\\nmodel - facebook/opt-350m\\nmax-model-len - 2048\\nsparsity - None\\nbenchmark_serving {\\n \\\"nr-qps-pair_\\\": \\\"300,1\\\",\\n \\\"dataset\\\": \\\"sharegpt\\\"\\n}\",\n \"benchmarking_context\": {\n \"vllm_version\": \"0.5.3.0\",\n \"python_version\": \"3.10.12 (main, Jun 7 2023, 13:43:11) [GCC 11.3.0]\",\n \"torch_version\": \"2.3.1+cu121\",\n \"torch_cuda_version\": \"12.1\",\n \"cuda_devices\": \"[_CudaDeviceProperties(name='NVIDIA H100 80GB HBM3', major=9, minor=0, total_memory=81116MB, multi_processor_count=132)]\",\n \"cuda_device_names\": [\n \"NVIDIA H100 80GB HBM3\"\n ]\n },\n \"gpu_description\": \"NVIDIA H100 80GB HBM3 x 1\",\n \"script_name\": \"benchmark_serving.py\",\n \"script_args\": {\n \"description\": \"VLLM Serving - Dense\\nmodel - facebook/opt-350m\\nmax-model-len - 2048\\nsparsity - None\\nbenchmark_serving {\\n \\\"nr-qps-pair_\\\": \\\"300,1\\\",\\n \\\"dataset\\\": \\\"sharegpt\\\"\\n}\",\n \"backend\": \"vllm\",\n \"version\": \"N/A\",\n \"base_url\": null,\n \"host\": \"127.0.0.1\",\n \"port\": 9000,\n \"endpoint\": \"/generate\",\n \"dataset\": \"sharegpt\",\n \"num_input_tokens\": null,\n \"num_output_tokens\": null,\n \"model\": \"facebook/opt-350m\",\n \"tokenizer\": \"facebook/opt-350m\",\n \"best_of\": 1,\n \"use_beam_search\": false,\n \"log_model_io\": false,\n \"seed\": 0,\n \"trust_remote_code\": false,\n \"disable_tqdm\": false,\n \"save_directory\": \"benchmark-results\",\n \"num_prompts_\": null,\n \"request_rate_\": null,\n \"nr_qps_pair_\": [\n 300,\n \"1.0\"\n ],\n \"server_tensor_parallel_size\": 1,\n \"server_args\": \"{'model': 'facebook/opt-350m', 'tokenizer': 'facebook/opt-350m', 'max-model-len': 2048, 'host': '127.0.0.1', 'port': 9000, 'tensor-parallel-size': 1, 'disable-log-requests': ''}\"\n },\n \"date\": \"2024-08-19 02:40:30 UTC\",\n \"model\": \"facebook/opt-350m\",\n \"dataset\": \"sharegpt\"\n}" - }, - { - "name": "{\"name\": \"mean_tpot_ms\", \"description\": \"VLLM Serving - Dense\\nmodel - facebook/opt-350m\\nmax-model-len - 2048\\nsparsity - None\\nbenchmark_serving {\\n \\\"nr-qps-pair_\\\": \\\"300,1\\\",\\n \\\"dataset\\\": \\\"sharegpt\\\"\\n}\", \"gpu_description\": \"NVIDIA H100 80GB HBM3 x 1\", \"vllm_version\": \"0.5.3.0\", \"python_version\": \"3.10.12 (main, Jun 7 2023, 13:43:11) [GCC 11.3.0]\", \"torch_version\": \"2.3.1+cu121\"}", - "value": 5.935463516049849, - "unit": "ms", - "extra": "{\n \"description\": \"VLLM Serving - Dense\\nmodel - facebook/opt-350m\\nmax-model-len - 2048\\nsparsity - None\\nbenchmark_serving {\\n \\\"nr-qps-pair_\\\": \\\"300,1\\\",\\n \\\"dataset\\\": \\\"sharegpt\\\"\\n}\",\n \"benchmarking_context\": {\n \"vllm_version\": \"0.5.3.0\",\n \"python_version\": \"3.10.12 (main, Jun 7 2023, 13:43:11) [GCC 11.3.0]\",\n \"torch_version\": \"2.3.1+cu121\",\n \"torch_cuda_version\": \"12.1\",\n \"cuda_devices\": \"[_CudaDeviceProperties(name='NVIDIA H100 80GB HBM3', major=9, minor=0, total_memory=81116MB, multi_processor_count=132)]\",\n \"cuda_device_names\": [\n \"NVIDIA H100 80GB HBM3\"\n ]\n },\n \"gpu_description\": \"NVIDIA H100 80GB HBM3 x 1\",\n \"script_name\": \"benchmark_serving.py\",\n \"script_args\": {\n \"description\": \"VLLM Serving - Dense\\nmodel - facebook/opt-350m\\nmax-model-len - 2048\\nsparsity - None\\nbenchmark_serving {\\n \\\"nr-qps-pair_\\\": \\\"300,1\\\",\\n \\\"dataset\\\": \\\"sharegpt\\\"\\n}\",\n \"backend\": \"vllm\",\n \"version\": \"N/A\",\n \"base_url\": null,\n \"host\": \"127.0.0.1\",\n \"port\": 9000,\n \"endpoint\": \"/generate\",\n \"dataset\": \"sharegpt\",\n \"num_input_tokens\": null,\n \"num_output_tokens\": null,\n \"model\": \"facebook/opt-350m\",\n \"tokenizer\": \"facebook/opt-350m\",\n \"best_of\": 1,\n \"use_beam_search\": false,\n \"log_model_io\": false,\n \"seed\": 0,\n \"trust_remote_code\": false,\n \"disable_tqdm\": false,\n \"save_directory\": \"benchmark-results\",\n \"num_prompts_\": null,\n \"request_rate_\": null,\n \"nr_qps_pair_\": [\n 300,\n \"1.0\"\n ],\n \"server_tensor_parallel_size\": 1,\n \"server_args\": \"{'model': 'facebook/opt-350m', 'tokenizer': 'facebook/opt-350m', 'max-model-len': 2048, 'host': '127.0.0.1', 'port': 9000, 'tensor-parallel-size': 1, 'disable-log-requests': ''}\"\n },\n \"date\": \"2024-08-19 02:40:30 UTC\",\n \"model\": \"facebook/opt-350m\",\n \"dataset\": \"sharegpt\"\n}" - } - ] - }, { "commit": { "author": { @@ -2242,6 +2196,52 @@ window.BENCHMARK_DATA = { "extra": "{\n \"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}\",\n \"benchmarking_context\": {\n \"vllm_version\": \"0.5.3.0\",\n \"python_version\": \"3.10.12 (main, Jun 7 2023, 13:43:11) [GCC 11.3.0]\",\n \"torch_version\": \"2.3.1+cu121\",\n \"torch_cuda_version\": \"12.1\",\n \"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)]\",\n \"cuda_device_names\": [\n \"NVIDIA A100-SXM4-80GB\",\n \"NVIDIA A100-SXM4-80GB\",\n \"NVIDIA A100-SXM4-80GB\",\n \"NVIDIA A100-SXM4-80GB\"\n ]\n },\n \"gpu_description\": \"NVIDIA A100-SXM4-80GB x 4\",\n \"script_name\": \"benchmark_serving.py\",\n \"script_args\": {\n \"description\": \"VLLM Serving - 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