[CI/Build] Add nightly benchmarking for tgi, tensorrt-llm and lmdeploy (#5362)
This commit is contained in:
Kuntai Du
221
.buildkite/nightly-benchmarks/scripts/run-vllm-nightly.sh
Normal file
221
.buildkite/nightly-benchmarks/scripts/run-vllm-nightly.sh
Normal file
@@ -0,0 +1,221 @@
|
||||
#!/bin/bash
|
||||
|
||||
set -o pipefail
|
||||
|
||||
check_gpus() {
|
||||
# check the number of GPUs and GPU type.
|
||||
declare -g gpu_count=$(nvidia-smi --list-gpus | wc -l)
|
||||
if [[ $gpu_count -gt 0 ]]; then
|
||||
echo "GPU found."
|
||||
else
|
||||
echo "Need at least 1 GPU to run benchmarking."
|
||||
exit 1
|
||||
fi
|
||||
declare -g gpu_type=$(echo $(nvidia-smi --query-gpu=name --format=csv,noheader) | awk '{print $2}')
|
||||
echo "GPU type is $gpu_type"
|
||||
}
|
||||
|
||||
kill_gpu_processes() {
|
||||
# kill all processes on GPU.
|
||||
pkill pt_main_thread
|
||||
sleep 10
|
||||
|
||||
# remove vllm config file
|
||||
rm -rf ~/.config/vllm
|
||||
|
||||
# Print the GPU memory usage
|
||||
# so that we know if all GPU processes are killed.
|
||||
gpu_memory_usage=$(nvidia-smi --query-gpu=memory.used --format=csv,noheader,nounits -i 0)
|
||||
# The memory usage should be 0 MB.
|
||||
echo "GPU 0 Memory Usage: $gpu_memory_usage MB"
|
||||
}
|
||||
|
||||
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"
|
||||
}
|
||||
|
||||
wait_for_server() {
|
||||
# wait for vllm server to start
|
||||
# return 1 if vllm server crashes
|
||||
timeout 1200 bash -c '
|
||||
until curl -s localhost:8000/v1/completions > /dev/null; do
|
||||
sleep 1
|
||||
done' && return 0 || return 1
|
||||
}
|
||||
|
||||
run_serving_tests() {
|
||||
# run serving tests using `benchmark_serving.py`
|
||||
# $1: a json file specifying serving test cases
|
||||
|
||||
local serving_test_file
|
||||
serving_test_file=$1
|
||||
|
||||
# Iterate over serving tests
|
||||
jq -c '.[]' "$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_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 $test_name."
|
||||
continue
|
||||
fi
|
||||
|
||||
# append vllm to the test name
|
||||
test_name=vllm_$test_name
|
||||
|
||||
|
||||
# get common parameters
|
||||
common_params=$(echo "$params" | jq -r '.common_parameters')
|
||||
model=$(echo "$common_params" | jq -r '.model')
|
||||
tp=$(echo "$common_params" | jq -r '.tp')
|
||||
dataset_name=$(echo "$common_params" | jq -r '.dataset_name')
|
||||
dataset_path=$(echo "$common_params" | jq -r '.dataset_path')
|
||||
port=$(echo "$common_params" | jq -r '.port')
|
||||
num_prompts=$(echo "$common_params" | jq -r '.num_prompts')
|
||||
|
||||
# get client and server arguments
|
||||
server_params=$(echo "$params" | jq -r '.vllm_server_parameters')
|
||||
client_params=$(echo "$params" | jq -r '.vllm_client_parameters')
|
||||
server_args=$(json2args "$server_params")
|
||||
client_args=$(json2args "$client_params")
|
||||
qps_list=$(echo "$params" | jq -r '.qps_list')
|
||||
qps_list=$(echo "$qps_list" | jq -r '.[] | @sh')
|
||||
echo "Running over qps list $qps_list"
|
||||
|
||||
# check if there is enough GPU to run the test
|
||||
if [[ $gpu_count -lt $tp ]]; then
|
||||
echo "Required tensor-parallel-size $tp but only $gpu_count GPU found. Skip testcase $test_name."
|
||||
continue
|
||||
fi
|
||||
|
||||
if echo "$common_params" | jq -e 'has("fp8")' > /dev/null; then
|
||||
echo "Key 'fp8' exists in common params. Use neuralmagic fp8 model for convenience."
|
||||
model=$(echo "$common_params" | jq -r '.neuralmagic_quantized_model')
|
||||
server_command="python3 \
|
||||
-m vllm.entrypoints.openai.api_server \
|
||||
-tp $tp \
|
||||
--model $model \
|
||||
--port $port \
|
||||
$server_args"
|
||||
else
|
||||
echo "Key 'fp8' does not exist in common params."
|
||||
server_command="python3 \
|
||||
-m vllm.entrypoints.openai.api_server \
|
||||
-tp $tp \
|
||||
--model $model \
|
||||
--port $port \
|
||||
$server_args"
|
||||
fi
|
||||
|
||||
# run the server
|
||||
echo "Running test case $test_name"
|
||||
echo "Server command: $server_command"
|
||||
eval "$server_command" &
|
||||
|
||||
# wait until the server is alive
|
||||
wait_for_server
|
||||
if [ $? -eq 0 ]; then
|
||||
echo ""
|
||||
echo "vllm server is up and running."
|
||||
else
|
||||
echo ""
|
||||
echo "vllm failed to start within the timeout period."
|
||||
break
|
||||
fi
|
||||
|
||||
# iterate over different QPS
|
||||
for qps in $qps_list; do
|
||||
# remove the surrounding single quote from qps
|
||||
if [[ "$qps" == *"inf"* ]]; then
|
||||
echo "qps was $qps"
|
||||
qps="inf"
|
||||
echo "now qps is $qps"
|
||||
fi
|
||||
|
||||
new_test_name=$test_name"_qps_"$qps
|
||||
|
||||
client_command="python3 benchmark_serving.py \
|
||||
--backend vllm \
|
||||
--model $model \
|
||||
--dataset-name $dataset_name \
|
||||
--dataset-path $dataset_path \
|
||||
--num-prompts $num_prompts \
|
||||
--port $port \
|
||||
--save-result \
|
||||
--result-dir $RESULTS_FOLDER \
|
||||
--result-filename ${new_test_name}.json \
|
||||
--request-rate $qps \
|
||||
$client_args"
|
||||
|
||||
echo "Running test case $test_name with qps $qps"
|
||||
echo "Client command: $client_command"
|
||||
|
||||
eval "$client_command"
|
||||
|
||||
# record the benchmarking commands
|
||||
jq_output=$(jq -n \
|
||||
--arg server "$server_command" \
|
||||
--arg client "$client_command" \
|
||||
--arg gpu "$gpu_type" \
|
||||
--arg engine "vllm" \
|
||||
'{
|
||||
server_command: $server,
|
||||
client_command: $client,
|
||||
gpu_type: $gpu,
|
||||
engine: $engine
|
||||
}')
|
||||
echo "$jq_output" >"$RESULTS_FOLDER/${new_test_name}.commands"
|
||||
|
||||
done
|
||||
|
||||
# clean up
|
||||
kill_gpu_processes
|
||||
rm -rf /root/.cache/huggingface/*
|
||||
done
|
||||
}
|
||||
|
||||
|
||||
upload_to_buildkite() {
|
||||
# upload the benchmarking results to buildkite
|
||||
|
||||
# if the agent binary is not found, skip uploading the results, exit 0
|
||||
if [ ! -f /workspace/buildkite-agent ]; then
|
||||
echo "buildkite-agent binary not found. Skip uploading the results."
|
||||
return 0
|
||||
fi
|
||||
# /workspace/buildkite-agent annotate --style "success" --context "benchmark-results" --append < $RESULTS_FOLDER/${CURRENT_LLM_SERVING_ENGINE}_nightly_results.md
|
||||
/workspace/buildkite-agent artifact upload "$RESULTS_FOLDER/*"
|
||||
}
|
||||
|
||||
main() {
|
||||
|
||||
check_gpus
|
||||
# enter vllm directory
|
||||
cd $VLLM_SOURCE_CODE_LOC/benchmarks
|
||||
declare -g RESULTS_FOLDER=results/
|
||||
mkdir -p $RESULTS_FOLDER
|
||||
BENCHMARK_ROOT=../.buildkite/nightly-benchmarks/
|
||||
|
||||
export CURRENT_LLM_SERVING_ENGINE=vllm
|
||||
run_serving_tests $BENCHMARK_ROOT/tests/nightly-tests.json
|
||||
|
||||
python3 -m pip install tabulate pandas
|
||||
python3 $BENCHMARK_ROOT/scripts/summary-nightly-results.py
|
||||
upload_to_buildkite
|
||||
|
||||
}
|
||||
|
||||
main "$@"
|
||||
Reference in New Issue
Block a user