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[CI] Add benchmark workflows (#1014)
### What this PR does / why we need it? Add benchmark workflows ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? Run locally --------- Signed-off-by: wangli <wangli858794774@gmail.com>
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‎.github/workflows/nightly_benchmarks.yaml‎

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#
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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# This file is a part of the vllm-ascend project.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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name: 'run benchmarks main'
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on:
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schedule:
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- cron: '00 16 * * *'
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workflow_dispatch:
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# after merged, secrets will be available
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# pull_request:
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# branches:
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# - 'main'
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# - '*-dev'
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# paths:
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# - '.github/workflows/nightly_benchmarks.yaml'
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# Bash shells do not use ~/.profile or ~/.bashrc so these shells need to be explicitly
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# declared as "shell: bash -el {0}" on steps that need to be properly activated.
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# It's used to activate ascend-toolkit environment variables.
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defaults:
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run:
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shell: bash -el {0}
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jobs:
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test:
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name: run benchmarks main
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runs-on: 'linux-arm64-npu-static-8'
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strategy:
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matrix:
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include:
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- vllm_branch: v0.9.0
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vllm_ascend_branch: main
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container:
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image: m.daocloud.io/quay.io/ascend/cann:8.1.rc1-910b-ubuntu22.04-py3.10
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volumes:
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- /usr/local/dcmi:/usr/local/dcmi
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- /usr/local/bin/npu-smi:/usr/local/bin/npu-smi
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- /usr/local/Ascend/driver/:/usr/local/Ascend/driver/
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# Use self-host cache speed up pip and model download
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- /home/action/.cache:/github/home/.cache/
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options: >-
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--device /dev/davinci0
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--device /dev/davinci1
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--device /dev/davinci_manager
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--device /dev/devmm_svm
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--device /dev/hisi_hdc
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env:
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HF_ENDPOINT: https://hf-mirror.com
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HF_TOKEN: ${{ secrets.HF_TOKEN }}
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ES_OM_DOMAIN: ${{ secrets.ES_OM_DOMAIN }}
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ES_OM_AUTHORIZATION: ${{ secrets.ES_OM_AUTHORIZATION }}
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steps:
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- name: Check npu and CANN info
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run: |
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npu-smi info
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cat /usr/local/Ascend/ascend-toolkit/latest/"$(uname -i)"-linux/ascend_toolkit_install.info
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- name: Config mirrors
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run: |
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pip config set global.index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
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- name: Install system dependencies
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run: |
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apt-get update -y
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apt-get -y install git jq wget curl lsof gcc g++ cmake libnuma-dev
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- name: Config git
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run: |
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git config --global --add safe.directory "$GITHUB_WORKSPACE"
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git config --global url."https://gh-proxy.test.osinfra.cn/https://github.com/".insteadOf https://github.com/
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- name: Checkout vllm-project/vllm-ascend repo
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uses: actions/checkout@v4
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with:
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ref: ${{ matrix.vllm_ascend_branch }}
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- name: Checkout vllm-project/vllm repo
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uses: actions/checkout@v4
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with:
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repository: vllm-project/vllm
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path: ./vllm-empty
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ref: ${{ matrix.vllm_branch }}
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- name: Install vllm-project/vllm from source
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working-directory: ./vllm-empty
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run: |
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VLLM_TARGET_DEVICE=empty pip install -e .
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- name: Install vllm-project/vllm-ascend
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run: |
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pip install -e .
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pip install -r benchmarks/requirements-bench.txt
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- name: Checkout cosdt/elastic-tool
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uses: actions/checkout@v4
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with:
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repository: cosdt/elastic-tool
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path: ./elastic_tool
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ref: 0.1.0-dev
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- name: Install elastic_tool
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working-directory: ./elastic_tool
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run: |
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pip install -e .
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- name: Collect pr info from vllm-project/vllm-ascend
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run: |
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# Only get the pull request which may influences performance
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git log --pretty=format:"%H %s" -- '**/*.py' ':!docs/*' ':!tests/*' ':!examples/*' > commit_log.txt
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escli check commit_log.txt
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- name: Run benchmark iteration
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run: |
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while IFS= read -r line || [[ -n "$line" ]]; do
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commit_id=${line%% *}
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commit_title=${line#* }
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commit_time=$(git show -s --format=%cd $commit_hash --date=iso-strict)
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commit_time_no_tz=${commit_time::19}
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git checkout $commit_id
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pip install -e .
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echo "------------------------"
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echo "commit_id: $commit_id"
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echo "commit_title: $commit_title"
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echo "commit_time: $commit_time_no_tz"
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echo "vllm branch: ${{ matrix.vllm_branch }}"
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echo "vllm-ascend branch: ${{ matrix.vllm_ascend_branch }}"
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echo "------------------------"
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bash benchmarks/scripts/run-performance-benchmarks.sh
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# send the result to es
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if [[ "${{ github.event_name }}" != "pull request" ]]; then
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escli add --vllm_branch ${{ matrix.vllm_branch }} \
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--vllm_ascend_branch ${{ matrix.vllm_ascend_branch }} \
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--commit_id $commit_id \
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--commit_title "$commit_title" \
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--created_at "$commit_time_no_tz" \
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--res_dir ./benchmarks/results
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rm -rf ./benchmarks/results
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fi
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done < commit_log.txt

‎benchmarks/scripts/run-performance-benchmarks.sh‎

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#!/bin/bash
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set -e
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check_npus() {
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# shellcheck disable=SC2155
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# wait for vllm server to start
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# return 1 if vllm server crashes
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timeout 1200 bash -c '
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until curl -X POST localhost:8000/v1/completions; do
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until curl -s -X POST localhost:8000/v1/completions || curl -s -X POST localhost:8000/v1/chat/completions; do
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sleep 1
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done' && return 0 || return 1
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}
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}
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update_json_field() {
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local json_file="$1"
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local field_name="$2"
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local field_value="$3"
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jq --arg value "$field_value" \
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--arg key "$field_name" \
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'.[$key] = $value' "$json_file" > "${json_file}.tmp" && \
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mv "${json_file}.tmp" "$json_file"
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}
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run_latency_tests() {
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# run latency tests using `benchmark_latency.py`
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# run the benchmark
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eval "$latency_command"
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# echo model_name to result file
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model_name=$(echo "$latency_params" | jq -r '.model')
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update_json_field "$RESULTS_FOLDER/${test_name}.json" "model_name" "$model_name"
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kill_npu_processes
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done
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# run the benchmark
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eval "$throughput_command"
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# echo model_name to result file
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model_name=$(echo "$throughput_params" | jq -r '.model')
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update_json_field "$RESULTS_FOLDER/${test_name}.json" "model_name" "$model_name"
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kill_npu_processes
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done
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rm -rf ./vllm_benchmarks
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}
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cleanup_on_error() {
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echo "An error occurred. Cleaning up results folder..."
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rm -rf $RESULTS_FOLDER
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}
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get_benchmarks_scripts() {
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git clone -b main --depth=1 git@github.com:vllm-project/vllm.git && \
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git clone -b main --depth=1 https://github.com/vllm-project/vllm.git && \
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mv vllm/benchmarks vllm_benchmarks
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rm -rf ./vllm
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}
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export VLLM_HOST_IP=$(hostname -I | awk '{print $1}')
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# turn of the reporting of the status of each request, to clean up the terminal output
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export VLLM_LOG_LEVEL="WARNING"
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# set env
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export VLLM_USE_MODELSCOPE="True"
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export HF_ENDPOINT="https://hf-mirror.com"
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# prepare for benchmarking
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declare -g RESULTS_FOLDER=results
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mkdir -p $RESULTS_FOLDER
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trap cleanup_on_error ERR
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ensure_sharegpt_downloaded
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# benchmarks
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run_serving_tests $QUICK_BENCHMARK_ROOT/tests/serving-tests.json

‎benchmarks/tests/latency-tests.json‎

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[
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{
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"test_name": "latency_llama8B_tp1",
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"test_name": "latency_qwen2_5vl_7B_tp1",
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"parameters": {
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"model": "LLM-Research/Meta-Llama-3.1-8B-Instruct",
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"model": "Qwen/Qwen2.5-VL-7B-Instruct",
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"tensor_parallel_size": 1,
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"load_format": "dummy",
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"max_model_len": 16384,
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"num_iters_warmup": 5,
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"num_iters": 15
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}
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},
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{
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"test_name": "latency_qwen2_5_7B_tp1",
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"test_name": "latency_qwen3_8B_tp1",
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"parameters": {
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"model": "Qwen/Qwen2.5-7B-Instruct",
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"model": "Qwen/Qwen3-8B",
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"tensor_parallel_size": 1,
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"load_format": "dummy",
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"max_model_len": 16384,
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"num_iters_warmup": 5,
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"num_iters": 15
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}

‎benchmarks/tests/serving-tests.json‎

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[
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{
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"test_name": "serving_llama8B_tp1",
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"test_name": "serving_qwen2_5vl_7B_tp1",
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"qps_list": [
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1,
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16,
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"inf"
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],
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"server_parameters": {
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"model": "LLM-Research/Meta-Llama-3.1-8B-Instruct",
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"model": "Qwen/Qwen2.5-VL-7B-Instruct",
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"tensor_parallel_size": 1,
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"swap_space": 16,
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"disable_log_stats": "",
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"disable_log_requests": "",
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"load_format": "dummy"
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"trust_remote_code": "",
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"max_model_len": 16384
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},
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"client_parameters": {
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"model": "LLM-Research/Meta-Llama-3.1-8B-Instruct",
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"backend": "vllm",
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"dataset_name": "sharegpt",
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"dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json",
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"model": "Qwen/Qwen2.5-VL-7B-Instruct",
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"backend": "openai-chat",
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"dataset_name": "hf",
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"hf_split": "train",
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"endpoint": "/v1/chat/completions",
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"dataset_path": "lmarena-ai/vision-arena-bench-v0.1",
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"num_prompts": 200
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}
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},
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{
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"test_name": "serving_qwen2_5_7B_tp1",
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"test_name": "serving_qwen3_8B_tp1",
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"qps_list": [
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1,
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4,
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16,
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"inf"
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],
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"server_parameters": {
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"model": "Qwen/Qwen2.5-7B-Instruct",
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"model": "Qwen/Qwen3-8B",
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"tensor_parallel_size": 1,
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"swap_space": 16,
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"disable_log_stats": "",
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"disable_log_requests": "",
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"load_format": "dummy"
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},
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"client_parameters": {
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"model": "Qwen/Qwen2.5-7B-Instruct",
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"model": "Qwen/Qwen3-8B",
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"backend": "vllm",
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"dataset_name": "sharegpt",
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"dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json",
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"dataset_path": "/root/.cache/datasets/sharegpt/ShareGPT_V3_unfiltered_cleaned_split.json",
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"num_prompts": 200
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}
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}

‎benchmarks/tests/throughput-tests.json‎

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[
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{
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"test_name": "throughput_llama8B_tp1",
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"test_name": "throughput_qwen3_8B_tp1",
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"parameters": {
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"model": "LLM-Research/Meta-Llama-3.1-8B-Instruct",
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"model": "Qwen/Qwen3-8B",
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"tensor_parallel_size": 1,
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"load_format": "dummy",
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"dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json",
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"dataset_path": "/root/.cache/datasets/sharegpt/ShareGPT_V3_unfiltered_cleaned_split.json",
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"num_prompts": 200,
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"backend": "vllm"
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}
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},
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{
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"test_name": "throughput_qwen2_5_7B_tp1",
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"test_name": "throughput_qwen2_5vl_7B_tp1",
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"parameters": {
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"model": "Qwen/Qwen2.5-7B-Instruct",
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"model": "Qwen/Qwen2.5-VL-7B-Instruct",
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"tensor_parallel_size": 1,
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"load_format": "dummy",
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"dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json",
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"num_prompts": 200,
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"backend": "vllm"
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"backend": "vllm-chat",
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"dataset_name": "hf",
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"hf_split": "train",
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"max_model_len": 16384,
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"dataset_path": "lmarena-ai/vision-arena-bench-v0.1",
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"num_prompts": 200
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}
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}
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]

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