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vllm/.buildkite/performance-benchmarks/scripts/run-performance-benchmarks.sh

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#!/bin/bash
# This script assumes that we are already inside the vllm/ directory
# Benchmarking results will be available inside vllm/benchmarks/results/
# Do not set -e, as the mixtral 8x22B model tends to crash occasionally
# and we still want to see other benchmarking results even when mixtral crashes.
set -x
set -o pipefail
# Environment-driven debug controls (like ON_CPU=1)
DRY_RUN="${DRY_RUN:-0}"
MODEL_FILTER="${MODEL_FILTER:-}"
DTYPE_FILTER="${DTYPE_FILTER:-}"
check_gpus() {
if command -v nvidia-smi; then
# check the number of GPUs and GPU type.
declare -g gpu_count=$(nvidia-smi --list-gpus | grep -c . || true)
elif command -v amd-smi; then
declare -g gpu_count=$(amd-smi list | grep -c 'GPU' || true)
elif command -v hl-smi; then
declare -g gpu_count=$(hl-smi --list | grep -ci "Module ID" || true)
fi
if [[ $gpu_count -gt 0 ]]; then
echo "GPU found."
else
echo "Need at least 1 GPU to run benchmarking."
exit 1
fi
declare -g arch_suffix=''
if command -v nvidia-smi; then
declare -g gpu_type=$(nvidia-smi --query-gpu=name --format=csv,noheader | awk '{print $2}')
elif command -v amd-smi; then
declare -g gpu_type=$(amd-smi static -g 0 -a | grep 'MARKET_NAME' | awk '{print $2}')
elif command -v hl-smi; then
declare -g gpu_type=$(hl-smi -q | grep "Product Name" | head -n 1 | awk -F ':' '{print $2}' | sed 's/^ *//')
arch_suffix='-hpu'
fi
echo "GPU type is $gpu_type"
}
check_cpus() {
# check the number of CPUs and NUMA Node and GPU type.
declare -g numa_count=$(lscpu | grep "NUMA node(s):" | awk '{print $3}')
if [[ $numa_count -gt 0 ]]; then
echo "NUMA found."
echo "$numa_count"
else
echo "Need at least 1 NUMA to run benchmarking."
exit 1
fi
if [[ "$(uname -m)" == "aarch64" ]] || [[ "$(uname -m)" == "arm64" ]]; then
declare -g gpu_type="arm64-cpu"
else
declare -g gpu_type="cpu"
fi
echo "GPU type is $gpu_type"
}
check_hf_token() {
# check if HF_TOKEN is available and valid
if [[ -z "$HF_TOKEN" ]]; then
echo "Error: HF_TOKEN is not set."
exit 1
elif [[ ! "$HF_TOKEN" =~ ^hf_ ]]; then
echo "Error: HF_TOKEN does not start with 'hf_'."
exit 1
else
echo "HF_TOKEN is set and valid."
fi
}
ensure_sharegpt_downloaded() {
local FILE=ShareGPT_V3_unfiltered_cleaned_split.json
if [ ! -f "$FILE" ]; then
wget https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/resolve/main/$FILE
else
echo "$FILE already exists."
fi
}
json2args() {
# transforms the JSON string to command line args, and '_' is replaced to '-'
# example:
# input: { "model": "meta-llama/Llama-2-7b-chat-hf", "tensor_parallel_size": 1 }
# output: --model meta-llama/Llama-2-7b-chat-hf --tensor-parallel-size 1
local json_string=$1
local args=$(
echo "$json_string" | jq -r '
to_entries |
map("--" + (.key | gsub("_"; "-")) + " " + (.value | tostring)) |
join(" ")
'
)
echo "$args"
}
json2envs() {
# transforms the JSON string to environment variables.
# example:
# input: { "VLLM_CPU_KVCACHE_SPACE": 5 }
# output: VLLM_CPU_KVCACHE_SPACE=5
local json_string=$1
local args=$(
echo "$json_string" | jq -r '
to_entries |
map((.key ) + "=" + (.value | tostring)) |
join(" ")
'
)
echo "$args"
}
wait_for_server() {
local timeout_val="1200"
timeout "$timeout_val" bash -c '
until curl -sf http://localhost:8000/v1/models >/dev/null; do
sleep 1
done
'
}
kill_processes_launched_by_current_bash() {
# Kill all python processes launched from current bash script
current_shell_pid=$$
processes=$(ps -eo pid,ppid,command | awk -v ppid="$current_shell_pid" -v proc="$1" '$2 == ppid && $3 ~ proc {print $1}')
if [ -n "$processes" ]; then
echo "Killing the following processes matching '$1':"
echo "$processes"
echo "$processes" | xargs kill -9
else
echo "No processes found matching '$1'."
fi
}
kill_gpu_processes() {
ps -aux
lsof -t -i:8000 | xargs -r kill -9
pgrep python3 | xargs -r kill -9
# vLLM now names the process with VLLM prefix after https://github.com/vllm-project/vllm/pull/21445
pgrep VLLM | xargs -r kill -9
# wait until GPU memory usage smaller than 1GB
if command -v nvidia-smi; then
while [ "$(nvidia-smi --query-gpu=memory.used --format=csv,noheader,nounits | head -n 1)" -ge 1000 ]; do
sleep 1
done
elif command -v amd-smi; then
while [ "$(amd-smi metric -g 0 | grep 'USED_VRAM' | awk '{print $2}')" -ge 1000 ]; do
sleep 1
done
elif command -v hl-smi; then
while [ "$(hl-smi -q | grep "Used" | head -n 1 | awk '{print $3}')" -ge 1000 ]; do
sleep 1
done
fi
# remove vllm config file
rm -rf ~/.config/vllm
}
upload_to_buildkite() {
# upload the benchmarking results to buildkite
# if the agent binary is not found, skip uploading the results, exit 0
# Check if buildkite-agent is available in the PATH or at /workspace/buildkite-agent
if command -v buildkite-agent >/dev/null 2>&1; then
BUILDKITE_AGENT_COMMAND="buildkite-agent"
elif [ -f /workspace/buildkite-agent ]; then
BUILDKITE_AGENT_COMMAND="/workspace/buildkite-agent"
else
echo "buildkite-agent binary not found. Skip uploading the results."
return 0
fi
# Use the determined command to annotate and upload artifacts
$BUILDKITE_AGENT_COMMAND annotate --style "info" --context "$BUILDKITE_LABEL-benchmark-results" < "$RESULTS_FOLDER/benchmark_results.md"
$BUILDKITE_AGENT_COMMAND artifact upload "$RESULTS_FOLDER/*"
}
run_benchmark_tests() {
# run benchmark tests using `vllm bench <test_type>` command
# $1: test type (latency or throughput)
# $2: a json file specifying test cases
local test_type=$1
local test_file=$2
# Iterate over tests
jq -c '.[]' "$test_file" | while read -r params; do
# get the test name, and append the GPU type back to it.
test_name=$(echo "$params" | jq -r '.test_name')
if [[ ! "$test_name" =~ ^${test_type}_ ]]; then
echo "In ${test_type}-test.json, test_name must start with \"${test_type}_\"."
exit 1
fi
# if TEST_SELECTOR is set, only run the test cases that match the selector
if [[ -n "$TEST_SELECTOR" ]] && [[ ! "$test_name" =~ $TEST_SELECTOR ]]; then
echo "Skip test case $test_name."
continue
fi
# get arguments
bench_params=$(echo "$params" | jq -r '.parameters')
bench_args=$(json2args "$bench_params")
bench_environment_variables=$(echo "$params" | jq -r '.environment_variables')
bench_envs=$(json2envs "$bench_environment_variables")
# check if there is enough GPU to run the test
tp=$(echo "$bench_params" | jq -r '.tensor_parallel_size')
if [[ "$ON_CPU" == "1" ]]; then
pp=$(echo "$bench_params" | jq -r '.pipeline_parallel_size // 1')
world_size=$(($tp*$pp))
if [[ $numa_count -lt $world_size && -z "${REMOTE_HOST}" ]]; then
echo "Required world-size $world_size but only $numa_count NUMA nodes found. Skip testcase $test_name."
continue
fi
else
if [[ $gpu_count -lt $tp ]]; then
echo "Required tensor-parallel-size $tp but only $gpu_count GPU found. Skip testcase $test_name."
continue
fi
fi
bench_command=" $bench_envs vllm bench $test_type \
--output-json $RESULTS_FOLDER/${test_name}.json \
$bench_args"
echo "Running test case $test_name"
echo "${test_type^} command: $bench_command"
# recording benchmarking command and GPU command
jq_output=$(jq -n \
--arg command "$bench_command" \
--arg gpu "$gpu_type" \
--arg test_type "$test_type" \
'{
($test_type + "_command"): $command,
gpu_type: $gpu
}')
echo "$jq_output" >"$RESULTS_FOLDER/$test_name.commands"
# run the benchmark
eval "$bench_command"
kill_gpu_processes
done
}
run_latency_tests() { run_benchmark_tests "latency" "$1"; }
run_startup_tests() { run_benchmark_tests "startup" "$1"; }
run_throughput_tests() { run_benchmark_tests "throughput" "$1"; }
merge_serving_tests_stream() {
# Emit merged serving test objects, optionally filtered by MODEL_FILTER/DTYPE_FILTER in DRY_RUN mode.
# This helper does NOT modify JSON; it only filters the stream in dry-run mode.
local serving_test_file="$1"
# shellcheck disable=SC2016
local merged='
if type == "array" then
# Plain format: test cases array
.[]
elif (type == "object" and has("tests")) then
# merge the default parameters into each test cases
. as $root
| ($root.defaults // {}) as $d
| ($root.tests // [])[]
# default qps / max_concurrency from defaults if missing
| .qps_list = (.qps_list // $d.qps_list)
| .max_concurrency_list = (.max_concurrency_list // $d.max_concurrency_list)
# merge envs / params: test overrides defaults
| .server_environment_variables =
(($d.server_environment_variables // {}) + (.server_environment_variables // {}))
| .server_parameters =
(($d.server_parameters // {}) + (.server_parameters // {}))
| .client_parameters =
(($d.client_parameters // {}) + (.client_parameters // {}))
else
error("Unsupported serving test file format: must be array or object with .tests")
end
'
jq -c "$merged" "$serving_test_file" | \
if [[ "${DRY_RUN:-0}" == "1" && ( "${MODEL_FILTER}${DTYPE_FILTER}" != "" ) ]]; then
jq -c --arg model "$MODEL_FILTER" --arg dtype "$DTYPE_FILTER" '
select((($model|length)==0)
or ((.server_parameters.model // "") == $model)
or ((.client_parameters.model // "") == $model))
| select((($dtype|length)==0) or ((.server_parameters.dtype // "") == $dtype))
'
else
cat
fi
}
run_serving_tests() {
# run serving tests using `vllm bench serve` command
# $1: a json file specifying serving test cases
#
# Supported JSON formats:
# 1) Plain format: top-level array
# [ { "test_name": "...", "server_parameters": {...}, ... }, ... ]
#
# 2) Default parameters field + plain format tests
# {
# "defaults": { ... },
# "tests": [ { "test_name": "...", "server_parameters": {...}, ... }, ... ]
# }
local serving_test_file
serving_test_file=$1
# In dry-run mode, if filters are provided but no tests match, fail fast.
if [[ "${DRY_RUN:-0}" == "1" && ( "${MODEL_FILTER}${DTYPE_FILTER}" != "" ) ]]; then
local count
count=$(merge_serving_tests_stream "$serving_test_file" | wc -l | tr -d ' ')
if [[ "$count" -eq 0 ]]; then
echo "No matching serving tests found in $serving_test_file for model='$MODEL_FILTER' dtype='$DTYPE_FILTER'." >&2
return 0
fi
fi
# Iterate over serving tests (merged + optional filtered stream)
merge_serving_tests_stream "$serving_test_file" | while read -r params; do
# get the test name, and append the GPU type back to it.
test_name=$(echo "$params" | jq -r '.test_name')
if [[ ! "$test_name" =~ ^serving_ ]]; then
echo "In serving-test.json, test_name must start with \"serving_\"."
exit 1
fi
# if TEST_SELECTOR is set, only run the test cases that match the selector
if [[ -n "$TEST_SELECTOR" ]] && [[ ! "$test_name" =~ $TEST_SELECTOR ]]; then
echo "Skip test case $test_name."
continue
fi
# get client and server arguments (after merged the default parameters)
server_params=$(echo "$params" | jq -r '.server_parameters')
server_envs=$(echo "$params" | jq -r '.server_environment_variables')
client_params=$(echo "$params" | jq -r '.client_parameters')
server_args=$(json2args "$server_params")
server_envs=$(json2envs "$server_envs")
client_args=$(json2args "$client_params")
# qps_list
qps_list=$(echo "$params" | jq -r '.qps_list')
qps_list=$(echo "$qps_list" | jq -r '.[] | @sh')
echo "Running over qps list $qps_list"
# max_concurrency_list (fallback to num_prompts if missing)
max_concurrency_list=$(echo "$params" | jq -r '.max_concurrency_list')
if [[ -z "$max_concurrency_list" || "$max_concurrency_list" == "null" ]]; then
num_prompts=$(echo "$client_params" | jq -r '.num_prompts')
max_concurrency_list="[$num_prompts]"
fi
max_concurrency_list=$(echo "$max_concurrency_list" | jq -r '.[] | @sh')
echo "Running over max concurrency list $max_concurrency_list"
# check if there is enough resources to run the test
tp=$(echo "$server_params" | jq -r '.tensor_parallel_size')
if [[ "$ON_CPU" == "1" ]]; then
pp=$(echo "$server_params" | jq -r '.pipeline_parallel_size // 1')
world_size=$(($tp*$pp))
if [[ $numa_count -lt $world_size && -z "${REMOTE_HOST}" ]]; then
echo "Required world-size $world_size but only $numa_count NUMA nodes found. Skip testcase $test_name."
continue
fi
else
if [[ $gpu_count -lt $tp ]]; then
echo "Required tensor-parallel-size $tp but only $gpu_count GPU found. Skip testcase $test_name."
continue
fi
fi
# check if server model and client model is aligned
server_model=$(echo "$server_params" | jq -r '.model')
client_model=$(echo "$client_params" | jq -r '.model')
if [[ $server_model != "$client_model" ]]; then
echo "Server model and client model must be the same. Skip testcase $test_name."
continue
fi
server_command="$server_envs vllm serve \
$server_args"
# run the server
echo "Running test case $test_name"
echo "Server command: $server_command"
# support remote vllm server
client_remote_args=""
if [[ -z "${REMOTE_HOST}" && "${DRY_RUN:-0}" != "1" ]]; then
bash -c "$server_command" &
server_pid=$!
# wait until the server is alive
if wait_for_server; then
echo ""
echo "vLLM server is up and running."
else
echo ""
echo "vLLM failed to start within the timeout period."
fi
elif [[ "${DRY_RUN:-0}" == "1" ]]; then
# dry-run: don't start server
echo "Dry Run."
else
server_command="Using Remote Server $REMOTE_HOST $REMOTE_PORT"
if [[ ${REMOTE_PORT} ]]; then
client_remote_args=" --host=$REMOTE_HOST --port=$REMOTE_PORT "
else
client_remote_args=" --host=$REMOTE_HOST "
fi
fi
# save the compilation mode and optimization level on the serving results
# whenever they are set
compilation_config_mode=$(echo "$server_params" | jq -r '."compilation_config.mode" // empty')
optimization_level=$(echo "$server_params" | jq -r '.optimization_level // empty')
# iterate over different QPS
for qps in $qps_list; do
# remove the surrounding single quote from qps
if [[ "$qps" == *"inf"* ]]; then
qps="inf"
fi
# iterate over different max_concurrency
for max_concurrency in $max_concurrency_list; do
new_test_name="${test_name}_qps_${qps}_concurrency_${max_concurrency}"
echo " new test name $new_test_name"
# pass the tensor parallel size, the compilation mode, and the optimization
# level to the client so that they can be used on the benchmark dashboard
client_command="vllm bench serve \
--save-result \
--result-dir $RESULTS_FOLDER \
--result-filename ${new_test_name}.json \
--request-rate $qps \
--max-concurrency $max_concurrency \
--metadata tensor_parallel_size=$tp compilation_config.mode=$compilation_config_mode optimization_level=$optimization_level \
$client_args $client_remote_args "
echo "Running test case $test_name with qps $qps"
echo "Client command: $client_command"
if [[ "${DRY_RUN:-0}" != "1" ]]; then
bash -c "$client_command"
fi
# record the benchmarking commands
jq_output=$(jq -n \
--arg server "$server_command" \
--arg client "$client_command" \
--arg gpu "$gpu_type" \
'{
server_command: $server,
client_command: $client,
gpu_type: $gpu
}')
echo "$jq_output" >"$RESULTS_FOLDER/${new_test_name}.commands"
done
done
# clean up
if [[ "${DRY_RUN:-0}" != "1" ]]; then
kill -9 "$server_pid"
kill_gpu_processes
fi
done
}
main() {
local ARCH
ARCH=''
if [[ "$ON_CPU" == "1" ]]; then
check_cpus
ARCH="-$gpu_type"
else
check_gpus
ARCH="$arch_suffix"
fi
# DRY_RUN does not execute vLLM; do not require HF_TOKEN.
if [[ "${DRY_RUN:-0}" != "1" ]]; then
check_hf_token
else
echo "DRY_RUN=1 -> skip HF_TOKEN validation"
fi
# dependencies
(which wget && which curl) || (apt-get update && apt-get install -y wget curl)
(which jq) || (apt-get update && apt-get -y install jq)
(which lsof) || (apt-get update && apt-get install -y lsof)
# get the current IP address, required by `vllm bench serve` command
export VLLM_HOST_IP=$(hostname -I | awk '{print $1}')
# turn of the reporting of the status of each request, to clean up the terminal output
export VLLM_LOGGING_LEVEL="WARNING"
# prepare for benchmarking
cd benchmarks || exit 1
ensure_sharegpt_downloaded
declare -g RESULTS_FOLDER=results/
mkdir -p $RESULTS_FOLDER
QUICK_BENCHMARK_ROOT=../.buildkite/performance-benchmarks/
# dump vllm info via vllm collect-env
env_output=$(vllm collect-env)
echo "$env_output" >"$RESULTS_FOLDER/vllm_env.txt"
# benchmarking
run_serving_tests $QUICK_BENCHMARK_ROOT/tests/"${SERVING_JSON:-serving-tests$ARCH.json}" || exit $?
if [[ "${DRY_RUN:-0}" == "1" ]]; then
echo "DRY_RUN=1 -> skip latency/startup/throughput suites"
exit 0
fi
run_latency_tests $QUICK_BENCHMARK_ROOT/tests/"${LATENCY_JSON:-latency-tests$ARCH.json}"
run_startup_tests $QUICK_BENCHMARK_ROOT/tests/"${STARTUP_JSON:-startup-tests$ARCH.json}"
run_throughput_tests $QUICK_BENCHMARK_ROOT/tests/"${THROUGHPUT_JSON:-throughput-tests$ARCH.json}"
# postprocess benchmarking results
pip install tabulate pandas
python3 $QUICK_BENCHMARK_ROOT/scripts/convert-results-json-to-markdown.py
upload_to_buildkite
}
main "$@"