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chore: Refine git source permissions #541

chore: Refine git source permissions

chore: Refine git source permissions #541

Workflow file for this run

# Runs the test suite on a self-hosted GPU machine with CUDA and OpenCL enabled
name: GPU tests
on:
pull_request:
types: [opened, synchronize, reopened, ready_for_review]
branches: [main]
merge_group:
env:
CARGO_TERM_COLOR: always
# Disable incremental compilation.
#
# Incremental compilation is useful as part of an edit-build-test-edit cycle,
# as it lets the compiler avoid recompiling code that hasn't changed. However,
# on CI, we're not making small edits; we're almost always building the entire
# project from scratch. Thus, incremental compilation on CI actually
# introduces *additional* overhead to support making future builds
# faster...but no future builds will ever occur in any given CI environment.
#
# See https://matklad.github.io/2021/09/04/fast-rust-builds.html#ci-workflow
# for details.
CARGO_INCREMENTAL: 0
# Allow more retries for network requests in cargo (downloading crates) and
# rustup (installing toolchains). This should help to reduce flaky CI failures
# from transient network timeouts or other issues.
CARGO_NET_RETRY: 10
RUSTUP_MAX_RETRIES: 10
# Don't emit giant backtraces in the CI logs.
RUST_BACKTRACE: short
RUSTFLAGS: -D warnings
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
cuda:
name: Rust tests on CUDA
if: github.event_name != 'pull_request' || github.event.action == 'enqueued'
runs-on: [self-hosted, gpu-ci]
env:
NVIDIA_VISIBLE_DEVICES: all
NVIDIA_DRIVER_CAPABILITITES: compute,utility
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- uses: dtolnay/rust-toolchain@stable
- uses: taiki-e/install-action@nextest
- uses: Swatinem/rust-cache@v2
# Check we have access to the machine's Nvidia drivers
- run: nvidia-smi
# The `compute`/`sm` number corresponds to the Nvidia GPU architecture
# In this case, the self-hosted machine uses the Ampere architecture, but we want this to be configurable
# See https://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/
- name: Set env for CUDA compute
run: echo "CUDA_ARCH=$(nvidia-smi --query-gpu=compute_cap --format=csv,noheader | sed 's/\.//g')" >> $GITHUB_ENV
- name: set env for EC_GPU
run: echo 'EC_GPU_CUDA_NVCC_ARGS=--fatbin --gpu-architecture=sm_${{ env.CUDA_ARCH }} --generate-code=arch=compute_${{ env.CUDA_ARCH }},code=sm_${{ env.CUDA_ARCH }}' >> $GITHUB_ENV
- run: echo "${{ env.EC_GPU_CUDA_NVCC_ARGS}}"
# Check that CUDA is installed with a driver-compatible version
# This must also be compatible with the GPU architecture, see above link
- run: nvcc --version
- name: CUDA tests
env:
EC_GPU_FRAMEWORK: cuda
run: |
cargo nextest run --profile ci --cargo-profile dev-ci --features cuda
opencl:
name: Rust tests on OpenCL
if: github.event_name != 'pull_request' || github.event.action == 'enqueued'
runs-on: [self-hosted, gpu-ci]
env:
NVIDIA_VISIBLE_DEVICES: all
NVIDIA_DRIVER_CAPABILITITES: compute,utility
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
- uses: dtolnay/rust-toolchain@stable
- uses: taiki-e/install-action@nextest
- uses: Swatinem/rust-cache@v2
# Check we have access to the machine's Nvidia drivers
- run: nvidia-smi
# The `compute`/`sm` number corresponds to the Nvidia GPU architecture
# In this case, the self-hosted machine uses the Ampere architecture, but we want this to be configurable
# See https://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/
- name: Set env for CUDA compute
run: echo "CUDA_ARCH=$(nvidia-smi --query-gpu=compute_cap --format=csv,noheader | sed 's/\.//g')" >> $GITHUB_ENV
- name: set env for EC_GPU
run: echo 'EC_GPU_CUDA_NVCC_ARGS=--fatbin --gpu-architecture=sm_${{ env.CUDA_ARCH }} --generate-code=arch=compute_${{ env.CUDA_ARCH }},code=sm_${{ env.CUDA_ARCH }}' >> $GITHUB_ENV
- run: echo "${{ env.EC_GPU_CUDA_NVCC_ARGS}}"
# Check that CUDA is installed with a driver-compatible version
# This must also be compatible with the GPU architecture, see above link
- run: nvcc --version
# Check that we can access the OpenCL headers
- run: clinfo
- name: OpenCL tests
env:
EC_GPU_FRAMEWORK: opencl
run: |
cargo nextest run --profile ci --cargo-profile dev-ci --features cuda,opencl