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open-mpi/ompi

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Ompi

Features

  • MPI Standard Implementations - Implements the full Message Passing Interface standard for portable parallel computing across heterogeneous systems.
  • Collective Communication Operations - Implements collective communication operations like broadcast, reduce, and barrier for parallel processes.
  • Distributed Computing Frameworks - Coordinates multiple processes across nodes to execute parallel programs using the MPI standard.
  • Process Grouping Utilities - Organizes distributed processes into logical units for isolated communication and data exchange.

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  • Parallel Process Communication Libraries - Manages process groups and communicators to control communication scope and topology in parallel environments.
  • Point-to-Point Communication Primitives - Ships point-to-point communication primitives for direct data transfer between specific processes.
  • Inter-Process Messaging - Exchanges data between parallel processes using point-to-point and collective communication routines.
  • Communicator-Based Process Groupings - Provides communicator-based process grouping to define communication domains for parallel execution.
  • High-Performance Computing - Executes computationally intensive scientific simulations across multiple nodes in a cluster.
  • MPI Parallel Computing Frameworks - Provides a complete framework for running parallel programs across distributed systems using the MPI standard.
  • MPI-Based Parallel Program Executions - Coordinates multiple processes across distributed nodes to run parallel computations using the MPI standard.
  • One-Sided Put/Get Operations - Provides one-sided put/get operations for direct remote memory access between parallel processes.
  • Thread-Safe Communication Channels - Provides thread-safe communication channels supporting concurrent message operations from multiple threads.
  • Runtime Process Spawners - Supports spawning and connecting new processes at runtime for flexible parallel job composition.
  • Fault Tolerance Implementation - Implements fault tolerance with user-defined error handlers and dynamic reconnection for parallel processes.
  • Build Systems - A high-performance implementation of the Message Passing Interface.
  • Parallel Programming - Implementation of the Message Passing Interface.
  • Windows Environments - Listed in the “Windows Environments” section of the Awesome C awesome list.
    • 2,527 stars·946 forks·C·other·19 views

    Star history

    Star history chart for open-mpi/ompiStar history chart for open-mpi/ompi

    How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

    Frequently asked questions

    What are the main features of open-mpi/ompi?

    The main features of open-mpi/ompi are: MPI Standard Implementations, Collective Communication Operations, Distributed Computing Frameworks, Process Grouping Utilities, Parallel Process Communication Libraries, Point-to-Point Communication Primitives, Inter-Process Messaging, Communicator-Based Process Groupings.

    Which projects share features with open-mpi/ompi?

    Projects with overlapping indexed features include: zhaochenyang20/awesome-ml-sys-tutorial — This project provides a comprehensive technical guide and framework for engineering large-scale machine learning… nvidia/nccl — NCCL is a high-performance communication library and distributed GPU computing framework designed for executing… boostorg/boost — Boost is a collection of portable, high-performance source libraries that extend the C++ standard library. It provides… parallel101/course — This project is a technical curriculum and set of educational resources focused on parallel programming,… dask/dask — Dask is a parallel computing framework and distributed task scheduler designed to scale Python data science workflows… stas00/ml-engineering — This project is a comprehensive engineering framework and technical reference for managing, scaling, and optimizing…

    Projects sharing features with Ompi

    These projects share indexed features with Ompi. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
    • zhaochenyang20/awesome-ml-sys-tutorialzhaochenyang20 avatar

      zhaochenyang20/Awesome-ML-SYS-Tutorial

      5,371View on GitHub↗

      This project provides a comprehensive technical guide and framework for engineering large-scale machine learning systems. It covers the full lifecycle of model development, focusing on the infrastructure and computational principles required to build, train, and serve generative AI models across distributed GPU clusters. The repository distinguishes itself by offering deep-dive tutorials and implementation strategies for complex system challenges. It emphasizes high-performance architectural primitives, such as collective communication orchestration, distributed tensor sharding, and static gr

      Python
      View on GitHub↗5,371
    • nvidia/ncclNVIDIA avatar

      NVIDIA/nccl

      5,213View on GitHub↗

      NCCL is a high-performance communication library and distributed GPU computing framework designed for executing collective and point-to-point data exchanges across multiple GPUs in single or multi-node systems. It serves as an RDMA GPU transport layer and memory orchestrator, facilitating high-bandwidth synchronization of data and model gradients for distributed GPU training and inference. The library is distinguished by its ability to execute communication primitives directly from GPU kernels, removing the host CPU from the critical path. It utilizes topology-aware path selection to optimize

      C++
      View on GitHub↗5,213
    • boostorg/boostboostorg avatar

      boostorg/boost

      8,493View on GitHub↗

      Boost is a collection of portable, high-performance source libraries that extend the C++ standard library. It provides a wide range of reusable components, data structures, and algorithms designed to add capabilities to the base language across different platforms. The project is distinguished by its extensive focus on compile-time template metaprogramming and generic programming. It implements advanced architectural patterns such as policy-based design, concept-based type validation, and the use of SFINAE for conditional template resolution to minimize runtime overhead. The library covers a

      HTML
      View on GitHub↗8,493
    • parallel101/courseparallel101 avatar

      parallel101/course

      4,233View on GitHub↗

      This project is a technical curriculum and set of educational resources focused on parallel programming, high-performance computing, and systems programming. It provides a structured course covering the implementation of parallel algorithms and multithreading techniques for processing large datasets. The project includes a systems programming guide for modern language features, a framework for lock-free concurrency patterns, and a manual for optimizing CPU and GPU performance through assembly analysis and cache management. The material covers hardware performance tuning, the implementation o

      C++coursecppcpp17
      View on GitHub↗4,233
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