TritonBench nightly (A100) #1
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name: TritonBench nightly (A100) | |
on: | |
workflow_dispatch: | |
schedule: | |
- cron: '00 18 * * *' # run at 6:00 PM UTC, K8s containers will roll out at 12PM EST | |
jobs: | |
run-benchmark: | |
environment: docker-s3-upload | |
env: | |
BASE_CONDA_ENV: "torchbench" | |
CONDA_ENV: "tritonbench-nightly" | |
PLATFORM_NAME: "gcp_a100" | |
SETUP_SCRIPT: "/workspace/setup_instance.sh" | |
TORCHBENCH_USERBENCHMARK_SCRIBE_GRAPHQL_ACCESS_TOKEN: ${{ secrets.TORCHBENCH_USERBENCHMARK_SCRIBE_GRAPHQL_ACCESS_TOKEN }} | |
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }} | |
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }} | |
IS_GHA: 1 | |
BUILD_ENVIRONMENT: benchmark-nightly | |
if: ${{ github.repository_owner == 'pytorch' }} | |
runs-on: [a100-runner] | |
steps: | |
- name: Checkout TorchBench | |
uses: actions/checkout@v3 | |
with: | |
path: benchmark | |
- name: Tune Nvidia GPU | |
run: | | |
sudo nvidia-smi -pm 1 | |
sudo nvidia-smi -ac 1215,1410 | |
nvidia-smi | |
sudo ldconfig | |
- name: Clone and setup conda env | |
run: | | |
CONDA_ENV=${BASE_CONDA_ENV} . "${SETUP_SCRIPT}" | |
conda create --name "${CONDA_ENV}" --clone "${BASE_CONDA_ENV}" | |
- name: Run the triton userbenchmark ci | |
run: | | |
. "${SETUP_SCRIPT}" | |
# remove old results if any | |
if [ -d benchmark-output ]; then rm -Rf benchmark-output; fi | |
pushd benchmark | |
if [ -d .userbenchmark ]; then rm -Rf .userbenchmark; fi | |
python run_benchmark.py triton --ci | |
cp -r ./.userbenchmark/triton ../benchmark-output | |
- name: Copy artifact and upload to scribe and Amazon S3 | |
run: | | |
. "${SETUP_SCRIPT}" | |
pushd benchmark | |
LATEST_RESULT=$(find ../benchmark-output/ -name "metrics-*.json" | sort -r | head -1) | |
echo "Benchmark result file: ${LATEST_RESULT}" | |
# Upload the result json to Scribe | |
python ./scripts/userbenchmark/upload_scribe.py --userbenchmark_json "${LATEST_RESULT}" --userbenchmark_platform "${PLATFORM_NAME}" | |
# Upload the result json to Amazon S3 | |
python ./scripts/userbenchmark/upload_s3.py --upload-file "${LATEST_RESULT}" --userbenchmark_platform "${PLATFORM_NAME}" | |
- name: Upload result to GH Actions Artifact | |
uses: actions/upload-artifact@v4 | |
with: | |
name: TritonBench result | |
path: benchmark-output/ | |
- name: Clean up Conda env | |
if: always() | |
run: | | |
. "${SETUP_SCRIPT}" | |
conda deactivate && conda deactivate | |
conda remove -n "${CONDA_ENV}" --all |