Intel® MPI Library Developer Guide for Linux* OS

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ID 768728
Date 6/24/2024
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Document Table of Contents
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 See Also 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 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

Running an MPI Program

Before running an MPI program, place it to a shared location and make sure it is accessible from all cluster nodes. Alternatively, you can have a local copy of your program on all the nodes. In this case, make sure the paths to the program match.

Run the MPI program using the mpirun command. The command line syntax is as follows: 

$ mpirun -n <number-of-processes> -ppn <processes-per-node> -f <hostfile> ./myprog

For example: 

$ mpirun -n 4 -ppn 2 -f hosts  ./myprog

In the command line above:

  • -n sets the number of MPI processes to launch; if the option is not specified, the process manager pulls the host list from a job scheduler, or uses the number of cores on the machine.
  • -ppn sets the number of processes to launch on each node; if the option is not specified, processes are assigned to the physical cores on the first node; if the number of cores is exceeded, the next node is used.
  • -f specifies the path to the host file listing the cluster nodes; alternatively, you can use the -hosts option to specify a comma-separated list of nodes; if hosts are not specified, the local node is used.
  • myprog is the name of your MPI program.

The mpirun command is a wrapper around the mpiexec.hydra command, which invokes the Hydra process manager. Consequently, you can use all mpiexec.hydra options with the mpirun command.

For the list of all available options, run mpirun with the -help option, or see section mpiexec.hydra in the Intel® MPI Library Developer Reference.

NOTE:
The commands mpirun and mpiexec.hydra are interchangeable. However, you are recommended to use the mpirun command for the following reasons:
  • You can specify all mpiexec.hydra options with the mpirun command.
  • The mpirun command detects if the MPI job is submitted from within a session allocated using a job scheduler like PBS Pro* or LSF*. Thus, you are recommended to use mpirun when an MPI program is running under a batch scheduler or job manager.
Parent topic: Running Applications
Level Two Title