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Create a workflow to run benchmarks #64

Create a workflow to run benchmarks

Create a workflow to run benchmarks #64

Workflow file for this run

name: Benchmarks
on:
pull_request:
branches:
- main
workflow_dispatch:
inputs:
halt-for-connection:
description: 'Should this workflow run wait for a remote connection?'
type: choice
required: true
default: 'no'
options:
- 'yes'
- 'no'
jobs:
jax-build-and-test:
runs-on: linux-x86-g2-48-l4-4gpu # Use a GPU-enabled runner
container:
image: "gcr.io/tensorflow-testing/nosla-cuda12.3-cudnn9.1-ubuntu20.04-manylinux2014-multipython:latest"
env:
JAXCI_HERMETIC_PYTHON_VERSION: 3.11
steps:
- name: Checkout JAX Fork
uses: actions/checkout@v3
with:
repository: 'google-ml-infra/jax-fork'
path: jax-fork
- name: Install JAX Dependencies
working-directory: jax-fork
run: |
python -m pip install --upgrade pip
pip install pytest
pip install absl-py
pip install "jax[cuda12_pip]" # Adjust CUDA version if needed
pip install google-benchmark
- name: Run JAX Multiprocess GPU Test
working-directory: jax-fork
continue-on-error: true
run: python -m pytest tests/multiprocess_gpu_test.py
build-xla-gpu-and-test:
runs-on: linux-x86-g2-48-l4-4gpu # Use a GPU-enabled runner
container:
image: "gcr.io/tensorflow-testing/nosla-cuda12.3-cudnn9.1-ubuntu20.04-manylinux2014-multipython:latest"
options: --gpus all --privileged # Might need privileged mode, use with caution
steps:
- name: Checkout XLA
uses: actions/checkout@v3
with:
repository: openxla/xla # Replace with your fork if needed
path: xla
- name: Create results directory
working-directory: xla
run: mkdir -p results
- name: Get GPU spec
working-directory: xla
continue-on-error: true
run: nvidia-smi
- name: Configure XLA
working-directory: xla
run: ./configure.py --backend CUDA --nccl
- name: Set TF_CPP_MAX_VLOG_LEVEL
working-directory: xla
run: export TF_CPP_MAX_VLOG_LEVEL=1
- name: Check TF_CPP_MAX_VLOG_LEVEL
working-directory: xla
run: echo "$TF_CPP_MAX_VLOG_LEVEL"
- name: Build hlo_runner_main
working-directory: xla
run: bazel build -c opt --config=cuda --dynamic_mode=off //xla/tools/multihost_hlo_runner:hlo_runner_main
# - name: Wait For Connection
# uses: google-ml-infra/actions/ci_connection@main
# with:
# halt-dispatch-input: ${{ inputs.halt-for-connection }}
- name: Run HLO Module Benchmarks withg GPU in xla/tests/fuzz
working-directory: xla
continue-on-error: true
run: |
for file in xla/tests/fuzz/*.hlo; do
filename=$(basename "$file")
# Skip expected failed hlo files.
if [[ "$filename" == "rand_000060.hlo" || "$filename" == "rand_000067.hlo" || "$filename" == "rand_000072.hlo" ]]; then
echo "Skipping benchmark on $file"
continue
fi
echo "Running benchmark on $file" &> results/"$filename".log
./bazel-bin/xla/tools/multihost_hlo_runner/hlo_runner_main --device_type=gpu --use_spmd_partitioning "$file" &> results/"$filename".log
done
- name: Upload Results
uses: actions/upload-artifact@v4
with:
name: gpu-xla-benchmarks
path: xla/results