Continuous Integration (CI) Testing Maintenance Tasks

In Continuous Integration (CI) Testing, we described RAJA CI testing workflows. This section describes how to perform common RAJA CI testing maintenance tasks.

GitLab CI Tasks

The tasks in this section apply to GitLab CI testing on Livermore Computing (LC) platforms. LC folks and others maintain Confluence pages with a lot of useful information for setting up and maintaining GitLab CI for a project, mirroring a GitHub to GitLab, etc. Please refer to LC GitLab CI for such information.

Changing build and test configurations

The configurations that are tested in RAJA are defined by a Spack spec in one of two places, depending on whether it is shared with other projects or it is specific to RAJA. The details are described in Launching CI pipelines (step 2). Each spec contains information (compiler and version, build variants, etc.) that must be consistent with the build specs defined in the RADIUSS Spack Configs project, which also includes the RAJA Spack package. The RADIUSS Spack Configs project is included as a RAJA submodule in the RAJA/scripts directory.

Removing a configuration

To remove a RAJA-specific test configuration, simply delete the entry for it in the RAJA/.gitlab/jobs/<MACHINE>.yml file where it is defined. Here, MACHINE is the name of an LC platform where GitLab CI is run.

To remove a shared configuration, it must be removed from the appropriate gitlab/radiuss-jobs/<MACHINE>.yml file in the RADIUSS Spack Configs project. Create a branch there, remove the job entry, and create a pull request.

Important

The RADIUSS Spack Configs project is used by several other projects. When changing a shared configuration file, please make sure the change is OK with those other projects. Typically, shared configurations are only changed when it makes sense to update compilers for all projects, such as when system default compiler versions change.

Adding a configuration

To add a RAJA-specific test configuration, add an entry for it to the RAJA/.gitlab/jobs/<MACHINE>.yml file, where MACHINE is the name of the LC platform where it will be run. When adding a test configuration, it is important to note two items that must be specified properly:

• Each jobs must have a unique job label, which identifies it in the machine configuration file and also on a web page for a GitLab CI pipeline

• The Spack spec name identifies the compiler and version, compiler flags, build options, etc. must match an existing spec in the RADIUSS Spack Configs project. Also, the build options must be consistent with the variants defined in the RAJA package in that project.

For example, an entry for a build using the clang 12.0.1 compiler with CUDA 11.5.0 on the LC lassen machine would be something like this:

clang_12_0_1_cuda_11_5_0:
  variables:
    SPEC: " ~shared +openmp +tests +cuda cuda_arch=70 %clang@12.0.1 ^cuda@11.5.0"
  extends: .job_on_lassen

Here, we enable OpenMP and CUDA, both of which must be enabled to test those RAJA back-ends, and specify the CUDA target architecture ‘sm_70’.

To add a shared configuration, it must be added to the appropriate gitlab/radiuss-jobs/<MACHINE>.yml file in the RADIUSS Spack Configs project. Create a branch there, add the job entry, and create a pull request.

Important

The RADIUSS Spack Configs project is used by several other projects. When changing a shared configuration file, please make sure the change is OK with those other projects. Typically, shared configurations are only changed when it makes sense to update compilers for all projects, such as when system default compiler versions change.

Modifying a configuration

To change an existing configuration, change the relevant information in the configuration in the appropriate RAJA/.gitlab/jobs/<MACHINE>.yml file. Make sure to also modify the job label as needed, so it is descriptive of the configuration is unique with respect to the others that are being run.

To modify a shared configuration, it must be changed in the appropriate gitlab/radiuss-jobs/<MACHINE>.yml file in the RADIUSS Spack Configs project. Create a branch there, modify the job entry, and create a pull request.

Important

Build spec information used in RAJA GitLab CI pipelines must exist in the compilers.yaml file and/or packages.yaml file for the appropriate system type in the RADIUSS Spack Configs repo.

If the desired entry is not there, but exists in a newer version of the RADIUSS Spack Configs project, update the RAJA submodule to use the newer version. If the information does not exist in any version of the RADIUSS Spack Configs project, create a branch there, add the needed spec info, and create a pull request. Then, when that PR is merged, update the RAJA submodule for the RADIUSS Spack Configs project to the new version.

Changing run parameters

The parameters for each system/scheduler on which we run GitLab CI for RAJA, such as job time limits, resource allocations, etc. are defined in the RAJA/.gitlab/custom-jobs-and-variables.yml file. This information can remain as is, for the most part, and should not be changed unless absolutely necessary.

For example, sometimes a particular job will take longer to build and run than the default allotted time for jobs on a machine. In this case, the time for the job can be adjusted in the job entry in the associated RAJA/.gitlab/jobs/<MACHINE>.yml file. For example:

gcc_8_1_0:
variables:
  SPEC: " ${PROJECT_DANE_VARIANTS} %gcc@8.1.0 ${PROJECT_DANE_DEPS}"
  DANE_BUILD_AND_TEST_JOB_ALLOC: "--time=60 --nodes=1"
extends: .job_on_dane

This example sets the build and test allocation time to 60 minutes and the the run resource to one node.

Allowing failures

Sometimes a shared job configuration is known to fail for RAJA. To allow the job to fail without the CI check associated with it failing, we can annotate the job for this. For example:

ibm_clang_9_0_0:
  variables:
    SPEC: " ${PROJECT_LASSEN_VARIANTS} %clang@ibm.9.0.0 ${PROJECT_LASSEN_DEPS}"
  extends: .job_on_lassen
  allow_failure: true

Important

When a shared job needs to be modified for RAJA specifically, we call that “overriding”. The job label must be kept the same as for the shared job in the gitlab/radiuss-jobs/<MACHINE>.yml file in the RADIUSS Spack Configs, and the RAJA-specific job can be adapted. If you override a shared job, please add a comment to describe the change in the RAJA/.gitlab/jobs/<MACHINE>.yml file where the job is overridden.

Building the Intel clang + SYCL HIP compiler for use in CI

To run CI tests for the RAJA SYCL back-end on GitLab, we use the corona system and a custom Intel Clang compiler that we build ourselves to support SYCL for AMD GPUs. This compiler lives in the /usr/workspace/raja-dev/ folder so that it can be accessed by the service user account that we use to run our GitLab CI. Since the Intel compiler does not do releases in the typical sense (they simply update their repo every night), it may become necessary to periodically build a new version of the compiler to ensure that we are using the most up-to-date version available. The steps for building, installing, and running are shown here.

Building the Compiler

Important

Because Intel updates their compiler repo daily, it is possible that the head of the SYCL branch will fail to build. In the event that it does not build, try checking out an earlier commit. On the Intel/LLVM GitHub page, one can see which of their commits builds by checking the status badge next to each commit. Look for a commit that passes.

1. Load the module of the version of GCC headers that you want to use. For example, we typically use the system default, which on corona is gcc/10.3.1-magic:

   module load gcc/10.3.1-magic
   

2. Load the module of the version of ROCm that you want to use. For example:

   module load rocm/5.7.1
   

3. Clone the SYCL branch of Intel’s LLVM compiler:

   git clone https://github.com/intel/llvm -b sycl
   

4. cd into the LLVM folder:

   cd llvm
   

   In the event that the head of the sycl branch does not build, run git checkout <git sha> to checkout a version that does build.

5. Build the compiler.

   Note that in this example, we are using rocm5.7.1, but one can change the version they wish to use simply by changing the paths in the configure step

   1. Configure

   srun -n1 /usr/bin/python3 buildbot/configure.py --hip -o buildrocm5.7.1 \
   --cmake-gen "Unix Makefiles" \
   --cmake-opt=-DSYCL_BUILD_PI_HIP_ROCM_DIR=/opt/rocm-5.7.1 \
   --cmake-opt=-DSYCL_BUILD_PI_HIP_ROCM_INCLUDE_DIR=/opt/rocm-5.7.1/include \
   --cmake-opt=-DSYCL_BUILD_PI_HIP_ROCM_LIB_DIR=/opt/rocm-5.7.1/lib \
   --cmake-opt=-DSYCL_BUILD_PI_HIP_INCLUDE_DIR=/opt/rocm-5.7.1/include \
   --cmake-opt=-DSYCL_BUILD_PI_HIP_HSA_INCLUDE_DIR=/opt/rocm-5.7.1/hsa/include/hsa \
   --cmake-opt=-DSYCL_BUILD_PI_HIP_LIB_DIR=/opt/rocm-5.7.1/lib \
   --cmake-opt=-DUR_HIP_ROCM_DIR=/opt/rocm-5.7.1 \
   --cmake-opt=-DUR_HIP_INCLUDE_DIR=/opt/rocm-5.7.1/include \
   --cmake-opt=-DUR_HIP_HSA_INCLUDE_DIR=/opt/rocm-5.7.1/hsa/include/hsa \
   --cmake-opt=-DUR_HIP_LIB_DIR=/opt/rocm-5.7.1/lib
   

   2. Build

   srun -n1 /usr/bin/python3 buildbot/compile.py -o buildrocm5.7.1
   

6. Test the compiler

   Follow the steps in the Using the compiler section to test the installation

7. Install

1. The build step will install the compiler in the folder buildrocm<version>/install. Copy this folder to the /usr/workspace/raja-dev/ directory using the naming scheme clang_sycl_<git sha>_hip_gcc<version>_rocm<version>

2. Set the permissions of the folder, and everything in it to 750:

   chmod 750 /usr/workspace/raja-dev/<foldername>/ -R
   

3. Change the group of the folder and everything in it to raja-dev:

   chgrp raja-dev /usr/workspace/raja-dev/<foldername>/ -R
   

Using the compiler

1. Load the version of rocm that you used when building the compiler, for example:

   module load rocm/5.7.1
   

2. Navigate to the root of your local RAJA checkout space:

   cd /path/to/raja
   

3. Run the test config script:

   ./scripts/lc-builds/corona_sycl.sh /usr/workspace/raja-dev/clang_sycl_2f03ef85fee5_hip_gcc10.3.1_rocm5.7.1
   

   Note that at the time of writing, the newest compiler we had built was at clang_sycl_2f03ef85fee5_hip_gcc10.3.1_rocm5.7.1

4. cd into the generated build directory:

   cd {build directory}
   

5. Build the code and run the RAJA tests:

   make -j
   make test
   

Azure Pipelines and GitHub Actions CI Tasks

The tasks in this section apply to RAJA Azure Pipelines and GitHub Actions CI testing that was described in Azure Pipelines and GitHub Actions CI

Changing Builds/Container Images

The builds we run in Azure are defined in the RAJA/azure-pipelines.yml file.

The builds we run in GitHub Actions are defined in the RAJA/.github/workflows/build.yml file.

Linux/Docker

To update or add a new compiler / job to Azure Pipelines or GitHub Actions CI, we need to edit either the RAJA/azure-pipelines.yml file or the RAJA/.github/workflows/build.yml file and the RAJA/Dockerfile, if changes are needed there.

If we want to add a new Azure pipeline to build with compilerX, then in the RAJA/azure-pipelines.yml file we can add the job like so:

-job: Docker
  ...
  strategy:
    matrix:
      ...
      compilerX:
        docker_target: compilerX

Here, compilerX defines the name of a job in Azure. docker_target: compilerX defines a variable docker_target, which is used to determine which entry in the Dockerfile file to use, where the name after docker_target is the shorthand name of job in the Dockerfile file following the word AS.

Similarly, for GitHub Actions, we add the name of the job to the job list in the RAJA/.github/workflows/build.yaml file:

jobs:
build_docker:
  strategy:
    matrix:
      target: [..., compilerX]

In the RAJA/Dockerfile file, we add a section that defines the commands for the compilerX job, such as:

FROM ghcr.io/llnl/radiuss:compilerX-ubuntu-22.04 AS compilerX
ENV GTEST_COLOR=1
COPY . /home/raja/workspace
WORKDIR /home/raja/workspace/build
RUN cmake -DCMAKE_CXX_COMPILER=compilerX ... && \
    make -j 6 && \
    ctest -T test --output-on-failure && \
    make clean

Each of our docker builds is built up on a base image maintained in the RADIUSS Docker Project.

The base container images are shared by multiple projects and are rebuilt regularly. If bugs are fixed in the base images, the changes will be automatically propagated to all projects using them in their Docker builds.

Check RADIUSS Docker Project for a list of currently available images.

Windows / MacOS

We run our Windows and MacOS builds directly on the provided Azure machine instances. To change the versions, change the pool under -job: Windows or -job: Mac in the RAJA/azure-pipelines.yml file:

-job: Windows
  ...
  pool:
    vmImage: 'windows-2019'
  ...

-job: Mac
  ...
  pool:
    vmImage: 'macOS-latest'

Similarly, in GitHub Actions, we run our Windows and MacOS builds directly on the provided machine instances. To change the versions, change the appropriate lines in the RAJA/.github/workflows/build.yml file:

build_mac:
  runs-on: macos-latest
...

build_windows:
  runs-on: windows-latest
...

Changing Build/Run Parameters

Linux/Docker

We can edit the build and run configurations of each Docker build, by editing the appropriate line containing the RUN command in the RAJA/Dockerfile file. For example, we can change CMake options or change the parallel build value of make -j N for adjusting throughput.

Each base image is built using spack. For the most part the container environments are set up to run our CMake and build commands out of the box. However, there are a few exceptions where we may need to load compiler specific environment variables, such as for the Intel LLVM compiler. For example, this may appear as:

RUN /bin/bash -c "source /opt/intel/oneapi/setvars.sh 2>&1 > /dev/null && \
  cmake ..."

In these cases, it is important to include the double quotes in the correct locations.

Windows / MacOS

Windows and MacOS build / run parameters can be configured directly in the RAJA/azure-pipelines.yml or RAJA/.github/workflows/build.yml file. CMake options can be configured with CMAKE_EXTRA_FLAGS for each job. The -j value can also be edited directly in these files for each job.

RAJA Performance Suite CI Tasks

The RAJA Performance Suite project CI testing processes, directory/file structure, and dependencies are nearly identical to that for RAJA, which is described in Continuous Integration (CI) Testing. Specifically,

• The RAJA Performance Suite GitLab CI process is driven by the RAJAPerf/.gitlab-ci.yml file.

• The custom-jobs-and-variables.yml and subscribed-pipelines.yml files reside in the RAJAPerf/.gitlab directory.

• The build_and_test.sh script resides in the RAJAPerf/scripts/gitlab directory.

• The RAJAPerf/Dockerfile drives the Azure testing pipelines.

The Performance Suite GitLab CI uses the uberenv and radiuss-spack-configs versions located in the RAJA submodule to make the testing consistent across projects and avoid redundancy. This is reflected in the RAJAPerf/.uberenv_config.json file which point at the relevant RAJA submodule locations. That is the paths contain tpl/RAJA/....

Apart from these minor differences, all CI maintenance and development tasks for the RAJA Performance Suite follow the same pattern that is described in Continuous Integration (CI) Testing Maintenance Tasks.