Intel® MPI Library Developer Guide for Linux* OS

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ID 768728
Date 10/31/2024
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Document Table of Contents x
Intel® MPI Library Developer Guide for Linux* OS
Intel® MPI Library Developer Guide for Linux* OS x
Introduction Installation and Prerequisites Compiling and Linking Running Applications Debugging Applications Analysis and Tuning Troubleshooting Additional Supported Features Examples Notices and Disclaimers
Introduction x
Introducing Intel® MPI Library Conventions and Symbols Related Information
Installation and Prerequisites x
Installation Prerequisite Steps
Compiling and Linking x
Compiling an MPI Program Compilers Support ILP64 Support
Running Applications x
Running Intel® MPI Library in Containers Selecting a Library Configuration Running an MPI Program Running an MPI/OpenMP* Program MPMD Launch Mode Fabrics Control Job Schedulers Support Controlling Process Placement Java* MPI Applications Support
Running Intel® MPI Library in Containers x
Build a Singularity* Container for an MPI Application Run the Application with a Container
Fabrics Control x
Selecting Fabrics Libfabric* Support OFI* Providers Support
Debugging Applications x
Debugging Using -gtool for Debugging
Analysis and Tuning x
Displaying MPI Debug Information Tracing Applications Interoperability with Other Tools Through -gtool MPI Tuning
Troubleshooting x
Error Message: Bad Termination Error Message: No such file or Directory Error Message: Permission Denied Error Message: Fatal Error Error Message: Bad File Descriptor Error Message: Too Many Open Files Problem: High Memory Consumption Readings Problem: MPI Application Hangs Problem: Password Required Problem: Cannot Execute Binary File Problem: MPI limitation for Docker*
Additional Supported Features x
Asynchronous Progress Control Device-Initiated Communications Language Support Examples Notified One-Sided Communications Multiple Endpoints Support
Multiple Endpoints Support x
MPI_THREAD_SPLIT Programming Model Threading Runtimes Support Program Examples Code Change Guide
Examples x
async_progress_sample.c thread_split.cpp thread_split_omp_for.c thread_split_omp_task.c thread_split_pthreads.c
Intel® MPI Library Developer Guide for Linux* OS

Device-Initiated Communications

Intel® MPI Library supports device-initiated one-sided communications to provide you with the ability to perform communications directly from the kernels executed on GPU without interrupting the kernel.

This feature allows you to use the existing MPI primitives without changing semantics with SYCL*, OpenMP* offload, and Intel® Data Center GPU Max Series. To enable device-initiated communications, in addition to the I_MPI_OFFLOAD=1 environment variable, set I_MPI_OFFLOAD_ONESIDED_DEVICE_INITIATED=1.

The current version supports the next set of primitives available on the device:

  • Communication primitives:
    • MPI_Put
    • MPI_Get
  • Passive-target synchronization primitives:
    • MPI_Win_lock
    • MPI_Win_lock_all
    • MPI_Win_unlock
    • MPI_Win_unlock_all
    • MPI_Win_flush
    • MPI_Win_flush_all
  • Active-target synchronization primitives:
    • MPI_Win_fence
  • Window-query primitives and group management:
    • MPI_Win_get_attr
    • MPI_Win_shared_query
    • MPI_Win_get_group
    • MPI_Group_free
    • MPI_Group_size
  • Intel® MPI notified one-sided communication extension:
    • MPIX_Win_set_notify
    • MPIX_Win_get_notify
    • MPIX_Get_notify
    • MPIX_Put_notify

Language Support

  Communication Primitives Passive-Target Synchronization Primitives Active-Target Synchronization Primitives Window-Query Primitives and Group Management Intel® MPI Notified One-Sided Communication Extension
SYCL* Supported Supported Supported Supported Supported
C/OpenMP* Supported Supported Supported Supported Supported
F77*/OpenMP* Supported Supported Supported N/A N/A
F90*/OpenMP* Supported Supported Supported N/A N/A

Examples

You can modify your code to incorporate device-initiated communications: 

sycl::queue q;
MPI_Win win;
int peer_rank = X;
// Allocate device memory local to a process
int *buf = sycl::malloc_device<int>(size, q);
// Create a RMA-Window device memory
MPI_Win_create(buf, (MPI_Aint) size * sizeof(int),
                sizeof(int), MPI_INFO_NULL, MPI_COMM_WORLD, &win);
// SYCL automatically capture local variables 
q.submit([&](sycl::handler &h) {
    h.single_task([=]() {
        int var = 0;
        // Perfrom computations updating "var"
        // ...

        // Initiate communication from the device
        MPI_Win_lock(MPI_LOCK_SHARED, peer_rank, 0, win);
        MPI_Put(&var, 1, MPI_INT, peer_rank, 0, 1, MPI_INT, win);
        MPI_Win_unlock(peer_rank, win);
        // Continue computations on GPU
    );
}).wait();

According to the MPI-4.0 standard, you can call MPI_Win_shared_query for an RMA window constructed using any available window creation method. Using MPI_Win_shared_query, an application may efficiently implement any communication pattern using direct access to the device memory of the peer process.

Parent topic: Additional Supported Features
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