OpenMPI

The OpenMPI Project is an open source Message Passing Interface implementation that is developed and maintained by a consortium of academic, research, and industry partners. OpenMPI is therefore able to combine the expertise, technologies, and resources from all across the High Performance Computing community in order to build the best MPI library available. OpenMPI offers advantages for system and software vendors, application developers and computer science researchers.

Versions

You can load a specific version using one of the following:

module load OpenMPI/3.1.1-GCC-7.3.0-2.30  # part of the foss-2018b toolchain
module load OpenMPI/3.1.3-GCC-8.2.0-2.31.1  # part of the foss-2019a toolchain
module load OpenMPI/3.1.3-gcccuda-2019a  # part of the fosscuda-2019a toolchain
module load OpenMPI/3.1.4-GCC-8.3.0  # part of the foss-2019b toolchain
module load OpenMPI/3.1.4-gcccuda-2019b  # part of the fosscuda-2019b toolchain

See here for a brief guide to the new features in OpenMPI 3.x and here for a detailed view of the changes between OpenMPI versions.

Example

Consider the following source code (hello.c):

#include <mpi.h>
#include <stdio.h>

int main(int argc, char** argv) {
    // Initialize the MPI environment
    MPI_Init(NULL, NULL);

    // Get the number of processes
    int world_size;
    MPI_Comm_size(MPI_COMM_WORLD, &world_size);

    // Get the rank of the process
    int world_rank;
    MPI_Comm_rank(MPI_COMM_WORLD, &world_rank);

    // Get the name of the processor
    char processor_name[MPI_MAX_PROCESSOR_NAME];
    int name_len;
    MPI_Get_processor_name(processor_name, &name_len);

    // Print off a hello world message
    printf("Hello world from processor %s, rank %d out of %d processors\n",
           processor_name, world_rank, world_size);

    // Finalize the MPI environment.
    MPI_Finalize();
}

MPI_COMM_WORLD (which is constructed for us by MPI) encloses all of the processes in the job, so this call should return the amount of processes that were requested for the job.

Compile your source code by using on of the following commands:

mpic++ hello.cpp -o file
mpicxx hello.cpp -o file
mpicc hello.c -o file
mpiCC hello.c -o file

Interactive job submission

You can run your job interactively:

srun file

Your output would be something like:

Hello world from processor bessemer-node001.shef.ac.uk, rank 0 out of 1 processors

This is an expected behaviour since we did not specify the number of CPU cores when requesting our interactive session. You can request an interactive node with multiple cores (4 in this example) by using the command:

srun --ntasks=4 --pty bash -i

Please note that requesting multiple cores in an interactive node depends on the availability. During peak times, it is unlikely that you can successfully request a large number of cpu cores interactively. Therefore, it may be a better approach to submit your job non-interactively.

Non-interactive job submission

Write a shell script (minimal example) We name the script as ‘test.sh’:

#!/bin/bash
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=40

module load OpenMPI/3.1.3-GCC-8.2.0-2.31.1

srun --export=ALL file

Maximum 40 cores can be requested.

Submit your script by using the command:

sbatch test.sh

Your output would be something like:

Hello world from processor bessemer-node003.shef.ac.uk, rank 24 out of 40 processors
Hello world from processor bessemer-node002.shef.ac.uk, rank 5 out of 40 processors
...
Hello world from processor bessemer-node003.shef.ac.uk, rank 31 out of 40 processors
Hello world from processor bessemer-node003.shef.ac.uk, rank 32 out of 40 processors