{"categories":[{"label":"Distributed Computing","url":"https://skillfed.io/packages/category/system-distributed-computing/3"}],"enrichment":{"capability":"Provides a high-performance Message Passing Interface (MPI) implementation for parallel computing applications, with support for multiple network modules and process management.","skillfed_tags":["hpc","parallel-computing","message-passing"],"use_cases":["Compile and run parallel C/C++/Fortran applications on HPC clusters using standard MPI calls.","Set up a multi-node compute environment where applications communicate via message passing.","Deploy on Top 500 HPC systems or vendor-supported clusters (Intel, HPE, ParTec infrastructure).","Develop and test parallel algorithms that require inter-process communication across distributed nodes.","Integrate with existing HPC workflows that expect mpicc, mpiexec, and standard MPI headers."],"what_it_does":"MPICH is a production-grade implementation of the Message Passing Interface standard, widely deployed on HPC systems and supported by vendors including Intel and HPE. It provides the mpicc compiler wrapper, mpiexec process manager, and core MPI runtime needed to build and run parallel applications across single or multiple nodes. The package comes with the Hydra process manager by default and supports multiple network modules (OFI, UCX) for different interconnect hardware.\n\nTypical use involves configuring MPICH with a chosen device and network module, installing it to a shared filesystem path visible on all compute nodes, then using mpicc to compile parallel C/C++/Fortran code and mpiexec to launch jobs across the cluster. It is not a Python library in the traditional sense\u2014it is a system-level MPI runtime that Python applications can call into via bindings.","worth_installing":"Yes, if you are building or running parallel HPC applications on a cluster and need a widely-adopted, vendor-supported MPI implementation. No, if you are looking for a Python library for parallel computing\u2014this is a system runtime, not a Python package. Yes-with-conditions if you are unfamiliar with MPI or HPC: expect to configure and install to a shared filesystem, understand process management, and have appropriate compilers available."},"id":"mpich","links":{"html":"https://skillfed.io/packages/mpich","md":"https://skillfed.io/packages/mpich.md","pypi":"https://pypi.org/project/mpich/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-16","license_spdx":null,"license_treatment":"unclear","name":"mpich","python_support":"unspecified","summary":"A high performance implementation of MPI"},"popularity":{"monthly_downloads":91121,"position":13539,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"5.0.1.post1"}