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Open MPI

by Open MPI consortium · Library · also known as OpenMPI, ompi

Open-source implementation of the MPI message-passing standard used to run tightly coupled parallel programs across the nodes of a cluster

BSD-3-Clause-Open-MPI licenseOpen sourceFreeLocalSelf-hostedSelf-hostable
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Checked Nov 2, 2026

Overview

Open MPI is an open-source implementation of the Message Passing Interface (MPI) specification, developed and maintained by a consortium of academic, research and industry partners under a 3-clause BSD license variant. MPI is the standard programming model of high-performance computing: processes on different nodes exchange messages and collectives (broadcast, reduce, all-gather) through a library API, and Open MPI provides that library for C, C++ and Fortran programs together with the mpirun launcher (built on PRRTE and PMIx) that starts processes across hosts over SSH or under schedulers such as Slurm, PBS and LSF.

It supports Linux and macOS, many network transports from TCP to InfiniBand, and is packaged by Homebrew and most Linux distributions. On a cluster of Macs it is the usual way to launch MPI-style jobs, and MLX's distributed backend can use MPI as one of its communication options.

It is a low-level tool: there is no scheduling, fault tolerance is limited, and applications must be written explicitly for message passing, which makes it most relevant to scientific codes rather than general data processing.

Capabilities

  • MPI point-to-point and collective communication
  • mpirun launcher across hosts via SSH or batch schedulers
  • Support for many network transports
  • C, C++ and Fortran bindings
  • Runtime tuning through MCA parameters

Typical workflows

  1. Run a Fortran or C simulation across several nodes
  2. Launch MLX distributed jobs with MPI on a Mac cluster
  3. Integrate MPI jobs into a Slurm allocation

Strengths

  • Standards-based and portable across HPC systems
  • Permissive BSD license
  • Widely packaged and documented

Limitations

  • Applications must be written for message passing
  • No built-in scheduling or elasticity
  • Limited fault tolerance for node failures

Prerequisites

  • C/C++/Fortran toolchain
  • Passwordless SSH or a scheduler between nodes

Who it is for

  • Scientific and HPC developers
  • Operators of small compute clusters

Alternatives & comparison

  • Dask

    Python library for parallel and distributed computing that scales pandas, NumPy and custom task graphs from a laptop to a cluster

    Open sourceOpen source
  • Ray

    Open-source Python framework for distributing tasks, actors and ML workloads across a cluster, with libraries for data processing, training, tuning, serving and reinforcement learning

    Open sourceOpen source
  • Slurm Workload Manager

    Open-source cluster resource manager and job scheduler for Linux clusters, allocating nodes, launching jobs and managing queues on many HPC systems

    Open sourceOpen source
Compare Open MPI with its alternatives →

Sources & verification

Primary sources consulted for this record. Claims are tied to the fields each source supports; the automated link checker re-verifies every URL on a schedule.

Confidence
High
Reviewed
Nov 1, 2026
Links
Broken · Nov 2, 2026

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