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Open MPI

Open MPI is an open-source implementation of the Message Passing Interface (MPI) standard, providing a portable and high-performance library for parallel computing in distributed-memory environments.^[1] Developed and maintained by a consortium of academic, research, and industry partners, Open MPI originated in 2003 from collaborative discussions at high-performance computing conferences, leading to the merger of three prominent MPI projects: LAM/MPI (from Ohio State University and later the University of Notre Dame), LA-MPI (from Los Alamos National Laboratory), and FT-MPI (from the University of Tennessee and later the University of Stuttgart).^[2] The project's first code commit occurred on November 22, 2003, with active development commencing on January 5, 2004, aiming to create a production-quality, community-driven MPI implementation free from legacy constraints.^[2] Key features of Open MPI include full conformance to the MPI-3.1 standard, support for elements of MPI-4.0, thread safety, dynamic process spawning, and fault tolerance mechanisms, all enabled by its modular, component-based architecture that facilitates integration with diverse networks, operating systems, and job schedulers.^[1] Released under a permissive BSD license, it emphasizes portability, tunability, and high performance across heterogeneous HPC platforms, with ongoing releases such as version 5.0.8 ensuring compatibility with modern computing needs.^[1]

History

Origins and Formation

Open MPI emerged from the collaborative efforts of developers working on four established Message Passing Interface (MPI) implementations in the early 2000s. These included LAM/MPI, originally developed at the Ohio State University supercomputing center and later maintained at the University of Notre Dame; LA-MPI, created at Los Alamos National Laboratory; FT-MPI, developed at the University of Tennessee, Knoxville; and PACX-MPI, from the High Performance Computing Center Stuttgart (HLRS) and the University of Stuttgart.^[3] Rather than incrementally merging existing codebases, the project aimed to leverage the strengths of each—such as LAM/MPI's portability across Unix systems, LA-MPI's focus on high-performance interconnects, FT-MPI's fault tolerance features, and PACX-MPI's process aggregation capabilities—while building an entirely new implementation from scratch.^[4] The formation process began with informal discussions among these developers at high-performance computing conferences throughout 2003, culminating in a pivotal meeting at the SC2003 conference in Phoenix, Arizona. There, the group decided to initiate a unified project, recognizing the need for a modern, community-driven alternative to fragmented MPI efforts. This decision led to the creation of the initial Open MPI source code repository on November 22, 2003, with active development commencing on January 5, 2004.^[3] In late 2004, the project expanded further when a developer from the University of Tennessee team relocated to the University of Stuttgart, effectively integrating their expertise into the effort.^[5] From its inception, Open MPI's core objectives centered on delivering a free, open-source, production-quality MPI implementation that prioritized high performance, broad platform support, and active community involvement. The project sought to fully conform to the MPI-1 and MPI-2 standards, enabling robust support for parallel applications across diverse hardware environments, including clusters with Ethernet, InfiniBand, and shared-memory systems.^[4] This emphasis on modularity and extensibility was intended to foster ongoing contributions from academic and research institutions, setting the stage for a sustainable, high-impact tool in high-performance computing.^[5]

Major Releases and Milestones

Open MPI's development has progressed through a series of major releases that have enhanced its compliance with evolving MPI standards and incorporated key performance and functionality improvements. The project began with its first public release, version 1.0, in November 2005, providing a foundational implementation of the MPI-1.1 standard with support for basic message passing operations across distributed systems.^[6] This initial version laid the groundwork for the modular architecture that would facilitate future updates. The v1.x series, spanning from 2005 to 2012, marked a transition to full MPI-2.0 compliance, introducing features such as dynamic process management and parallel I/O capabilities.^[7] A significant milestone in this era was the integration of the hwloc library in version 1.3 (released in 2010), which enabled topology awareness to optimize process binding and resource allocation on multi-core systems.^[8] The series concluded with version 1.10 in 2012, solidifying Open MPI's reputation for robustness in high-performance computing environments.^[9] Subsequent releases advanced standard conformance further, with version 3.0 in September 2017 achieving full MPI-3.0 compliance, including support for non-blocking collectives and improved one-sided communications. Version 2.0, released in July 2016, introduced support for heterogeneous networks, allowing seamless operation across diverse interconnects like InfiniBand and Ethernet.^[10] Building on this, version 4.0 arrived in November 2018, providing full MPI-3.1 compliance and enhancements in performance and usability. The v5.0 series, launched in October 2023, brought enhancements in fault tolerance through the User-Level Fault Mitigation (ULFM) extension and improved thread safety for multi-threaded applications, along with initial support for elements of the MPI-4.0 standard. This series leverages Open MPI's component-based architecture to enable these advancements without breaking backward compatibility.^[11] As of November 2025, the latest stable releases include v5.0.9, a bug-fix update focused on stability (released October 30, 2025), and v4.1.8, which addresses library issues and includes updates for OpenSHMEM support. A key milestone in late 2025 is the SC25 conference presentation in November, highlighting new performance improvements and critical bug fixes in the ongoing development.^[12]

Technical Features

Supported Standards

Open MPI provides full conformance to the MPI-3.1 standard, which encompasses core communication primitives including point-to-point messaging for sending and receiving data between processes, collective operations for group-wide synchronization and data exchange, and one-sided communications enabling remote memory access without explicit receiver involvement.^[7]^[13] This conformance ensures robust support for established high-performance computing workflows that rely on these mechanisms for parallel application development.^[1] The implementation maintains backward compatibility with earlier MPI specifications, including MPI-1.0, MPI-1.1, MPI-2.0, and MPI-2.1, allowing legacy applications developed under these standards to execute without modification while leveraging Open MPI's modern optimizations.^[7] As of the v5.0.x series, Open MPI offers partial support for the MPI-4.0 standard, incorporating elements such as enhanced partitioned communications for scalable subgroup interactions and session management for dynamic process group handling.^[7]^[14] Beyond MPI, Open MPI integrates support for the OpenSHMEM standard starting from the v3.0.0 series, providing a partitioned global address space model for one-sided data transfers and collective operations in shared-memory-like environments.^[15] Additionally, it incorporates POSIX threads (pthreads) to enable multi-threaded execution, supporting all levels of MPI thread safety including MPI_THREAD_MULTIPLE for concurrent thread access to MPI calls.^[1] These standards facilitate hybrid programming models in high-performance computing applications, combining message passing with shared-memory parallelism.

Key Capabilities

Open MPI provides high-performance message passing for distributed-memory parallel computing systems, implementing core MPI primitives such as point-to-point communications via functions like MPI_Send and MPI_Recv, as well as collective operations including MPI_Bcast and MPI_Reduce, optimized for low latency and high bandwidth across clusters.^[7] These capabilities enable efficient data exchange in large-scale applications, leveraging modular run-time components to achieve scalable performance without requiring user-level modifications.^[16] A key usability feature is thread safety at the MPI_THREAD_MULTIPLE level, which allows multiple threads to make MPI calls concurrently without internal serialization, supporting hybrid parallel models that combine MPI with threading libraries like OpenMP.^[7] This is particularly beneficial in multi-core environments, where applications can overlap communication and computation for improved efficiency, though certain components like file operations remain non-thread-safe.^[7] Open MPI supports dynamic process spawning and management through MPI_Comm_spawn, enabling runtime creation of additional processes for adaptive parallelism in workflows that require variable resource allocation during execution.^[7] This facilitates flexible job scaling without restarting the entire application, integrating seamlessly with MPI communicators for ongoing coordination. For fault tolerance, Open MPI incorporates User-Level Fault Mitigation (ULFM) extensions, allowing applications to detect and recover from node failures using error codes such as MPIX_ERR_PROC_FAILED and APIs like MPIX_Comm_revoke and MPIX_Comm_shrink to revoke faulty processes and continue execution in a degraded but functional state.^[17] These mechanisms ensure that MPI calls do not block indefinitely post-failure, promoting resilient operation in unreliable large-scale systems, with full support in the ob1 point-to-point layer.^[17] Tunability in heterogeneous environments is achieved through configurable parameters and broad platform compatibility, supporting Linux, macOS, and Windows (via Cygwin) to run across mixed-OS clusters while handling differences in data types and endianness.^[18] Integration with job schedulers like SLURM and PBS is built-in, allowing seamless launching of MPI jobs via mpirun within allocated resources, with automatic detection of scheduler environments for optimized process placement.^[19]^[20] Network heterogeneity is addressed via multiple transport layers, including InfiniBand and RoCE through the UCX framework for remote direct memory access, Ethernet over TCP for standard IP networks, and shared memory for intra-node communications, enabling efficient hybrid fabrics in diverse HPC setups.^[21]^[22] This multi-fabric support allows users to select optimal interconnects at runtime, balancing performance and portability without code changes.^[23]

Architecture

Modular Design

Open MPI employs a modular, framework-based design centered on the Modular Component Architecture (MCA), which serves as the foundational structure for its functionality across MPI, OpenSHMEM, and related systems.^[24] This architecture organizes Open MPI into hierarchical layers: projects as top-level code divisions (such as OPAL for foundational utilities, OMPI for MPI-specific features, and OSHMEM for shared-memory operations), frameworks that manage task-specific components (for example, BTL for byte transfer layers and PML for point-to-point management layers), components as pluggable implementations within frameworks, and modules as runtime instances of those components.^[25] The MCA enables runtime selection of components through parameters, allowing dynamic loading of plugins to tailor the system without recompilation.^[26] A core aspect of this design is its extensibility, permitting users and vendors to add or replace components as standalone plugins without altering the core codebase.^[24] Licensed under the 3-clause BSD license, Open MPI facilitates broad adoption and modification by academic, research, and industry contributors, promoting collaborative development.^[27] This plugin-based approach ensures that new functionalities, such as support for emerging hardware, can be integrated seamlessly via the MCA framework. The benefits of this modular design include enhanced portability across diverse hardware environments, including GPUs, accelerators, and various network fabrics, by selecting appropriate components at runtime.^[24] It also reduces development time through reusable modules, enabling developers to focus on specialized extensions rather than rebuilding foundational elements.^[24] Key design principles underpinning the MCA emphasize separation of concerns, where lower-level elements like transport layers operate independently of upper-level APIs, and dynamic loading at runtime to optimize performance based on the execution environment.^[24] This structure not only supports efficient resource utilization but also maintains the integrity of Open MPI's core while accommodating vendor-specific optimizations.^[24]

Core Components

The core components of Open MPI form the foundational layers responsible for implementing MPI semantics, managing data transfers, and handling runtime operations. These components operate within the Modular Component Architecture (MCA), allowing interchangeable plugins to adapt to diverse hardware and network environments.^[28] The Point-to-Point Management Layer (PML) is the primary interface for handling MPI point-to-point communication semantics, such as sends and receives, by abstracting the underlying transport mechanisms. It ensures reliable message delivery and buffering while supporting features like eager and rendezvous protocols for small and large messages, respectively. Key variants include the ob1 PML, which provides basic operations using Byte Transfer Layers (BTLs) for multi-network support, and the cm PML, which focuses on dynamic connection management often paired with Matching Transport Layers (MTLs) for optimized performance on high-speed fabrics.^[28] The Byte Transfer Layer (BTL) serves as the low-level transport mechanism for intra-node and inter-node data movement, enabling efficient byte-level transfers across heterogeneous networks. For intra-node communication, the shared memory (sm) BTL facilitates high-bandwidth, low-latency exchanges between processes on the same host using memory mapping techniques, while the TCP BTL handles inter-node transfers over Ethernet networks with support for multiple connections to stripe large messages. These BTLs are selected and managed via the BTL Management Layer (BML) to optimize based on available hardware.^[28] The Runtime Environment (RTE), implemented as the PMIx Reference Runtime Environment (PRRTE) in Open MPI version 5.0.x and later, oversees process launching, resource allocation, monitoring, and termination across distributed systems. It integrates with external launchers like mpirun or mpiexec to bootstrap MPI jobs, manage process groups, and provide fault detection, replacing the earlier Open RTE (ORTE) for improved scalability in exascale environments. PRRTE leverages the Process Management Interface (PMIx) standard to exchange job information and coordinate with resource managers.^[29] Additional modules enhance specific functionalities, such as the collective (coll) framework, which implements MPI collective algorithms like broadcast and reduce using tunable components (e.g., basic or tuned) to select optimal topologies based on message size and communicator structure. Open MPI also integrates the Hardware Locality (hwloc) library for detecting and binding processes to hardware topology, with version 2.12.2 support introduced in releases around 2025 to improve affinity on multi-core and NUMA systems.^[28]^[30] In the interaction flow, user-level MPI calls are routed through the PML for point-to-point operations, which delegates to BTLs for actual data transport or to the RTE for process management; collective calls engage the coll framework, all underpinned by hwloc for locality optimization. This layered design, enabled by MCA modularity, allows seamless component swaps without recompilation.^[28]^[31]

Implementations and Usage

Open Source Distribution

Open MPI is primarily distributed through its official website at open-mpi.org, where users can download stable source code tarballs, and via the project's GitHub repository at github.com/open-mpi/ompi, which hosts the main development trunk for cloning and contribution. The source code is released under a permissive BSD license, allowing broad reuse and modification while requiring attribution to the original authors.^[1]^[32] Installation of Open MPI typically involves either compiling from source using its Autotools-based build system or utilizing pre-built binaries provided by package managers. For source compilation, users extract the tarball, run the configure script to customize options such as compiler selection and feature enables, and then execute make and make install commands, supporting a wide range of platforms including Linux, macOS, and Windows via Cygwin. Pre-built binaries are available for major Linux distributions through repositories like apt (e.g., openmpi-bin package on Debian/Ubuntu) or yum/dnf (e.g., on CentOS/RHEL), and for macOS via Homebrew with the brew install open-mpi command, simplifying deployment in development and production environments.^[20]^[33] The project's documentation, hosted at docs.open-mpi.org, provides comprehensive resources including user guides for installation and runtime configuration, API references through manual pages (e.g., mpirun and MPI function descriptions), and quick-start tutorials covering building, tuning for performance, and basic usage examples, all tailored to the v5.0.x series. These materials emphasize practical steps for integrating Open MPI into high-performance computing workflows.^[34]^[35] Version management in Open MPI follows a structured release model with stable versions in the v5.0.x series, such as v5.0.9 released on October 30, 2025, which receives ongoing maintenance and bug fixes as a long-term support branch. Additionally, nightly builds are generated from the GitHub main branch, offering early access to upcoming features and fixes for testing purposes, though they are not recommended for production use.^[11]

Commercial and Vendor Adaptations

Several high-performance computing (HPC) vendors have adopted and adapted Open MPI to enhance their hardware and software ecosystems, integrating its modular architecture to optimize performance on proprietary platforms.^[4] For instance, IBM's Spectrum MPI is a commercial implementation directly based on the Open MPI open-source project, providing a compliant MPI library with additional optimizations for scalability and performance on IBM Power Systems and x86 architectures.^[36] This adaptation includes proprietary extensions for better integration with IBM's hardware, such as advanced CPU affinity controls, while maintaining full compatibility with the MPI standard.^[37] HPE has incorporated Open MPI support into its Cray EX systems, enabling efficient communication over the Slingshot-11 interconnect through custom plugins and ABI compatibility layers that bridge Open MPI applications to HPE's native MPI environment.^[38] Similarly, NVIDIA (formerly Mellanox) provides optimized builds of Open MPI within its OFED software stack, leveraging InfiniBand and RoCE fabrics for low-latency, high-bandwidth messaging in GPU-accelerated clusters.^[39] These adaptations utilize hardware-specific accelerations, such as direct GPU memory access, to improve collective operations in large-scale simulations. Cisco has contributed to Open MPI, including support for usNIC to enable low-latency networking over Ethernet in UCS fabrics.^[40] The permissive 3-clause BSD license of Open MPI facilitates these commercial adaptations by allowing vendors to create proprietary forks without mandatory disclosure of modifications, enabling closed-source variants tailored for specific markets.^[27] For example, IBM Spectrum MPI represents such a fork.^[36] These deployments often emphasize scalability tuning, such as hierarchical collectives, to achieve efficient performance at exascale levels.^[41] Open MPI adaptations are widely deployed in industry-leading supercomputers and cloud-based HPC services as of 2025, powering scalable workloads on systems like those in the TOP500 list.^[1] In cloud environments, such as AWS ParallelCluster and Azure Batch, tuned versions of Open MPI support elastic scaling across virtual clusters, with performance optimizations ensuring low-overhead communication for distributed machine learning and scientific computing.^[42]

Consortium and Community

Founding and Member Organizations

Open MPI was founded in 2004 through the merger of several existing Message Passing Interface (MPI) implementations, forming a collaborative consortium to create a unified, high-performance open-source MPI platform.^[2] The founding members consisted of five core academic and research institutions: the University of Tennessee, Knoxville, which led overall development and contributed the FT-MPI fault-tolerant implementation; Los Alamos National Laboratory, which provided the LA-MPI codebase focused on scalability for large-scale systems; the University of Notre Dame, contributing the LAM/MPI implementation originally developed at Ohio State University's supercomputing center; Ohio State University, involved in early LAM/MPI work; and the University of Stuttgart, whose team joined in late 2004 to enhance modular components.^[2] By 2025, the Open MPI consortium had expanded significantly from its initial five founding teams to over 20 active contributing organizations, reflecting broad adoption across sectors.^[43] Academic members, such as Auburn University, the University of Houston, and the University of Stuttgart, emphasize research into MPI standards compliance and innovative algorithms.^[43] Research laboratories, including Los Alamos National Laboratory, Oak Ridge National Laboratory, and Sandia National Laboratories, contribute expertise in high-performance computing environments and fault tolerance.^[43] Industry partners like IBM, Intel, and NVIDIA provide essential funding, rigorous testing on specialized hardware such as GPUs and multi-node clusters, and optimizations for production workloads.^[43] This diverse membership structure enables Open MPI to balance cutting-edge research with practical deployment needs, with academic partners driving standards evolution while industry ensures compatibility and performance on commercial systems.^[43]

Governance and Contributions

Open MPI is governed by the Administrative Steering Committee (ASC), composed of representatives from member organizations who oversee project direction, release planning, and membership approvals through a voting process requiring a two-thirds majority and over 50% quorum.^[44] Core developers such as Jeff Squyres from Cisco Systems and Ralph Castain from Intel serve on the ASC as of 2025, guiding technical decisions and community coordination.^[45]^[46] The ASC conducts weekly teleconferences to solicit agenda items, discuss progress, and resolve issues, a practice established since the project's inception in 2004.^[44] Additionally, the project holds annual in-person meetings at the SC (Supercomputing) conferences to foster collaboration among developers and stakeholders.^[47]^[48] Contributions to Open MPI follow a structured process centered on its GitHub repository, where developers submit code changes, bug fixes, or features via pull requests targeting the main branch.^[49] Each submission must include a "Signed-off-by" declaration affirming adherence to the project's contributor license, followed by review from designated maintainers who evaluate compliance with coding standards, such as using 4-space indentation and specific C formatting rules.^[49]^[44] Approved contributions undergo testing across multiple platforms to ensure portability and reliability before integration.^[49] The Open MPI community emphasizes engagement through dedicated mailing lists for discussions and announcements, as well as GitHub issue trackers for reporting bugs and proposing enhancements.^[50]^[49] Contributors are recognized via the project's team listings and commit histories, with formal members gaining voting rights and commit privileges after signing agreements.^[43] The governance model promotes inclusivity by welcoming new developers with clear guidelines, encouraging diverse ideas, and accepting external plugins under the BSD license to broaden participation.^[49] Funding for Open MPI sustains its open-source development through U.S. Department of Energy (DOE) grants, such as those under the Exascale Computing Project for enhancements like OMPI-X, and National Science Foundation (NSF) awards supporting AI-driven improvements and efficiency upgrades as of 2025.^[51]^[52] Industry sponsorships from member organizations, including Cisco and Intel, provide additional resources for testing, hosting, and personnel.^[43] This mixed funding model ensures long-term sustainability while maintaining the project's commitment to open-source principles.^[43]

References

[1]
Open MPI: Open Source High Performance Computing
The Open MPI Project is an open source Message Passing Interface implementation that is developed and maintained by a consortium of academic, research, and ...DownloadDocumentationVersion 4.1MPISource Code Access
[2]
16. History of Open MPI
LAM/MPI: originally from the Ohio State University supercomputing center and later migrated to the University of Notre Dame.
[3]
16. History of Open MPI
Oct 30, 2025 · Open MPI represents the merger of three prior MPI implementations: LAM/MPI: originally from the Ohio State University supercomputing center and ...Missing: origins | Show results with:origins
[4]
[PDF] Goals, Concept, and Design of a Next Generation MPI Implementation
MPI, Open MPI represents more than a simple merger of LAM/MPI, LA-MPI and FT-MPI. Although influenced by previous code bases, Open MPI is an all- new ...Missing: origins SC2003
[5]
[PDF] What we've done and where we're going - Open MPI
□ Developers of FT-MPI, LA-MPI, LAM/MPI. ▫ Kept meeting at conferences in 2003. ▫ Culminated at SC 2003: Let's start over. ▫ Open MPI was born. □ Started ...Missing: origins merger
[6]
Version 1.0 - Open MPI
PLEASE NOTE: The 1.0 series of Open MPI is effectively dead. There was work beyond the last stable release (v1.0.2) in the Subversion repository that was never ...
[7]
3.6. MPI Functionality and Features — Open MPI 5.0.x documentation
3.6.1. MPI Standard conformance ... In the Open MPI v5.0.x series, all MPI-3.1 functionality is supported. Some MPI-4.0 functionality is supported. As such, ...
[8]
Portable Hardware Locality (hwloc): Version 1.3 - Open MPI
hwloc is distributed under the BSD license. This file contains a list of changes between the releases in the hwloc releases in the 1.3 series. Current stable ...Missing: integration | Show results with:integration
[9]
Version 1.10 - Open MPI
This file contains a list of changes between the releases in the Open MPI in the v1.10 series. See the version timeline for information on the chronology of ...
[10]
Version 2.0 - Open MPI
This file contains a list of changes between the releases in the Open MPI in the v2.0 series. See the version timeline for information on the chronology of Open ...
[11]
3.1.1. Open MPI v5.0.x series
This file contains all the NEWS updates for the Open MPI v5.0.x series, in reverse chronological order.
[12]
Version 5.0 - Open MPI
See the version timeline for information on the chronology of Open MPI releases. Current stable release downloads: Release, File names, Size, Date, Checksums ...Version Timeline · Version 4.1 · OpenMPI 3.1.4 · Version 2.1 (retired)
[13]
MPI: A Message-Passing Interface Standard Version 3.1
Version 3.1: June 4, 2015. This document contains mostly corrections and clarifications to the MPI-3.0 document. The largest change is a correction to the ...
[14]
[PDF] MPI: A Message-Passing Interface Standard
Jun 9, 2021 · Version MPI-4.0 (June 9, 2021) adds significant new features to MPI ... release of MPI-2.0, the MPI Forum kept working on errata and ...
[15]
[PDF] A Message-Passing Interface Standard - MPI Forum
Nov 2, 2023 · MPI-4.0 (June 9, 2021): Significant new features beyond MPI-3.1. • MPI-4.1 (November 2, 2023): Clarifications and minor extensions to MPI-4.0.
[16]
3.7. OpenSHMEM Functionality and Features - Open MPI
OpenSHMEM Functionality and Features . All OpenSHMEM-1.3 functionality is supported. Previous Next. © Copyright 2003-2025, The Open MPI Community.<|separator|>
[17]
5. Open MPI-specific features
Open MPI-specific features . Open MPI has multiple features that are above and beyond what is specified in the MPI Standard.Missing: key capabilities
[18]
5.3. User-Level Fault Mitigation (ULFM) - Open MPI
Fault Tolerance is enabled by default and is controlled with MCA variables. Added support for multithreaded modes (MPI_THREAD_MULTIPLE, etc.)
[19]
FAQ: What kinds of systems / networks / run-time environments does ...
Mar 28, 2022 · Does Open MPI support execution in heterogeneous environments? ... Open MPI 1.8 supports all of MPI-3. Starting with v2.0, Open MPI supports all ...
[20]
10.7. Launching with Slurm — Open MPI main documentation
Using mpirun is the recommended method for launching Open MPI jobs in Slurm jobs. mpirun 's Slurm support should always be available.
[21]
FAQ: Building Open MPI
Dec 4, 2024 · More generally, Open MPI supports a wide variety of hardware and environments, but it sometimes needs to be told where support libraries and ...What are the default build... · Where should I install Open...
[22]
3.10. Network Support — Open MPI main documentation
The main OpenSHMEM network model is ucx ; it interfaces directly with UCX. In prior versions of Open MPI, InfiniBand and RoCE support was provided through the ...
[23]
11.2.4. InifiniBand / RoCE support — Open MPI main documentation
UCX is an open-source optimized communication library which supports multiple networks, including RoCE, InfiniBand, uGNI, TCP, shared memory, and others.
[24]
11.2. Networking support — Open MPI main documentation
Open MPI supports a variety of different networking transports for off-node communication. Not all transports are supported or available on every platform.Missing: InfiniBand | Show results with:InfiniBand
[25]
8. The Modular Component Architecture (MCA) - Open MPI
The Modular Component Architecture (MCA) is the backbone for much of Open MPI's functionality. It is a series of projects, frameworks, components, and modules ...
[26]
https://docs.open-mpi.org/en/main/mca.html#selecting-which-open-mpi-components-are-used-at-run-time
[27]
https://www.open-mpi.org/community/license.php
[28]
Open MPI License
Mar 25, 2022 · Open MPI is distributed under the 3-clause BSD license, listed below. Most files in this release are marked with the copyrights of the organizations who have ...
[29]
13.8. Internal frameworks — Open MPI 5.0.x documentation
Here is a list of all the component frameworks in the MPI layer of Open MPI: bml : BTL management layer. coll : MPI collective algorithms. fbtl ...Missing: RTE | Show results with:RTE
[30]
10.3. The role of PMIx and PRRTE — Open MPI 5.0.x documentation
PRRTE has effectively replaced ORTE in the Open MPI implementation. Open MPI uses both of these external packages for its run-time system support. Both PMIx and ...
[31]
11.10. Tuning Collectives — Open MPI 5.0.x documentation
Open MPI's tuned collective component has three modes of operation, fixed decision, forced algorithm, and dynamic decision.
[32]
8. The Modular Component Architecture (MCA) - Open MPI
When Open MPI switched from using ORTE to PRRTE as its run-time environment, some MCA parameters were renamed to be more consistent and/or allow more flexible ...
[33]
open-mpi/ompi: Open MPI main development repository - GitHub
The Open MPI Project is an open source implementation of the Message Passing Interface (MPI) specification that is developed and maintained by a consortium of ...
[34]
4.2. Downloading Open MPI
Open MPI is generally available two ways: As source code. The best place to get an official Open MPI source code distribution is from the main Open MPI web site ...
[35]
17. Open MPI manual pages
Open MPI manual pages . All of the content in this section is also installed as individual manual (“man”) pages in an Open MPI installation.
[36]
Open MPI Documentation
Dec 21, 2024 · Prior stable release series. v4.1 series. This documentation reflects the latest progression in the 4.1.x series. Older series (retired ...MPI · V3.0 (retired) · V3.1 (retired) · V4.0 (retired)Missing: history | Show results with:history<|control11|><|separator|>
[37]
IBM Spectrum MPI - Overview
IBM Spectrum MPI features an Open MPI implementation for HPC parallel applications with improved performance and scalability. Supported on IBM Power Systems™, ...
[38]
[PDF] IBM Spectrum MPI: User's Guide - | HPC @ LLNL
For information about Open MPI, and to obtain official Open MPI documentation, refer to the Open MPI web site (www.open-mpi.org). This information assumes ...
[39]
[PDF] Open MPI for HPE Cray EX Systems
May 9, 2023 · Open MPI uses libfabric APIs to communicate with peers. At runtime, LINKx examines peer & selects best provider based on locality. Flow: LINKx ...
[40]
Introduction - NVIDIA Docs
Oct 23, 2023 · Mellanox OFED includes the following MPI implementation over InfiniBand: Open MPI – an open source MPI-2 implementation by the Open MPI Project.
[41]
Open MPI: behind the scenes - Cisco Blogs
Feb 9, 2015 · How can we reduce the memory footprint and resource consumption of Open MPI's core library? Most of Open MPI is fairly efficient, but there are ...
[42]
Recent improvement to Open MPI AllReduce and the impact to ...
Sep 24, 2024 · Our testing has shown that this effort can allow HPC customers to work with applications on AWS using Open MPI without any performance disadvantages.Missing: modex | Show results with:modex
[43]
[PDF] Bringing HPE Slingshot 11 Support to Open MPI - OSTI.GOV
The improvements resulted in point-to-point shared memory performance comparable to that of Cray MPICH, as shown in Figure 4(b). XPMEM support The Cray systems ...
[44]
The Open MPI Development Team
May 28, 2021 · The Open MPI project has 14 members, 4 partners, and 36 contributors, including 16 individuals and 38 organizations.Missing: joining | Show results with:joining
[45]
Administrative rules · open-mpi/ompi Wiki - GitHub
Oct 13, 2017 · All new Members must be nominated by a current Member of the Open MPI community and approved by the Administrative Steering Committee (ASC) ...
[46]
Jeff Squyres - Cisco Blogs
Dr. Jeff Squyres is Cisco's representative to the MPI Forum standards body and is Cisco's core software developer in the open source Open MPI project.
[47]
Ralph Castain | IEEE Xplore Author Details
Ralph Castain is currently serving as a Research Scientist within the Electrical and Computer Engineering Department at Colorado State University.
[48]
[PDF] Open MPI State of the Union Community Meeting SC'14
Nov 19, 2014 · v1.9 / v2.0 MPI conformance. • MPI-3.1 planned conformance for v1.9 series (not yet published). ▫ Various errata, non-blocking I/O. ▫ Will be ...<|control11|><|separator|>
[49]
[PDF] Open MPI State of the Union Community Meeting SC'11
Nov 16, 2011 · Community Meeting SC'11. Jeff Squyres. George Bosilca. Shinjii ... • Craig Rasmussen (Los Alamos National. Labs), Jeff Squyres (Cisco) ...
[50]
14. Contributing to Open MPI — Open MPI main documentation
This means being able to ensure that all code included in Open MPI is free, open source, and able to be distributed under the BSD license. Open MPI has ...Missing: website | Show results with:website
[51]
https://www.eurekalert.org/news-releases/477408
[52]
The Exascale Computing Project awards $34 million for software ...
Nov 10, 2016 · Open MPI for Exascale (OMPI-X), David Bernholdt, ORNL with LANL ... The ECP is a collaborative effort of two DOE organizations--the Office of ...
[53]
UT Collaborates on NSF Grants to Improve Outcomes Through AI
Aug 18, 2025 · ... Open MPI, a major open-source implementation of MPI with a long history of broad impact, to make it more efficient, flexible, and better ...