MPITestall

MPITestall is an open-source testing framework designed to automate the discovery, execution, and reporting of tests for MPI-based applications. It aims to provide a standardized workflow for validating MPI programs across heterogeneous compute environments, supporting multiple MPI runtimes such as Open MPI, MPICH, and MVAPICH. The project emphasizes reproducibility, scalability, and integration with common HPC tooling.

MPITestall originated as a community-driven effort in the early 2020s to address the need for consistent MPI testing across diverse clusters. It has since evolved through contributions from researchers, developers, and system administrators, with ongoing maintenance and governance shared by a global user and developer base. The project is typically hosted in a public source repository and welcomes new contributors under an open-source license.

Key features include test discovery and suite management, environment provisioning for local and remote execution, and multi-runtime support to run tests with different MPI implementations. It provides parallel test execution, centralized results collection, and reporting in multiple formats (for example JSON and XML), aiding integration with continuous integration pipelines. The framework can interface with common cluster managers and schedulers (such as SLURM and Grid Engine) and offers optional containerized execution through Docker or Singularity to improve portability. Configuration is commonly managed via manifest files or YAML/JSON schemas, allowing users to specify test suites, host sets, and runtime options.

Licensing and community: MPITestall is released under an open-source license, with a community-driven model for issues, feature requests, and contributions. It is used in academic research and industry to benchmark MPI deployments and validate MPI-enabled applications, though users typically require familiarity with MPI concepts and HPC environments.

See also: Message Passing Interface, Open MPI, MPICH, MVAPICH, MPI testing frameworks, high-performance computing.