Working with C++

The tutorial assumes you have already worked through the Execute a Job Tutorial. Therefore, the instructions here are abbreviated but will follow the same format so you may easily consult the extended tutorial.

Table of Contents

📝 Note: Do not execute jobs on the login nodes; only use the login nodes to access your compute nodes. Processor-intensive, memory-intensive, or otherwise disruptive processes running on login nodes will be killed without warning.

Step 1: Access the Onyx HPC

  1. Open a Bash terminal (or MobaXterm for Windows users).

  2. Execute ssh doaneusername@onyx.doane.edu.

  3. When prompted, enter your password.

Step 2: Create an sbatch Script

Example sbatch Script

Here is an example sbatch script for running a batch job on an HPC like Onyx.

#!/bin/bash

#SBATCH -n 16
#SBATCH -o test_%A.out
#SBATCH --error test_%A.err
#SBATCH --mail-user $CHANGE_TO_YOUR_EMAIL
#SBATCH --mail-type ALL

module purge
module load gnu/5.4.0
module load openmpi
module list

mpirun hello.mpi

sbatch Procedure

  1. Use nano or Vim (we use Vim here) to create and edit your sbatch script.

    vim slurm_mpi_example.job

  2. Create your sbatch script within Vim by typing i for insert mode or paste the contents of your sbatch script into Vim.

  3. Save your file by typing :wq! and return to the Bash shell.

Step 3: Compile the C++ Program from Source

MPI Hello World Source Code

/*
  "Hello World" MPI Test Program
*/
#include <assert.h>
#include <stdio.h>
#include <string.h>
#include <mpi.h>

int main(int argc, char **argv)
{
    char buf[256];
    int my_rank, num_procs;

    /* Initialize the infrastructure necessary for communication */
    MPI_Init(&argc, &argv);

    /* Identify this process */
    MPI_Comm_rank(MPI_COMM_WORLD, &my_rank);

    /* Find out how many total processes are active */
    MPI_Comm_size(MPI_COMM_WORLD, &num_procs);

    /* Until this point, all programs have been doing exactly the same.
       Here, we check the rank to distinguish the roles of the programs */
    if (my_rank == 0) {
        int other_rank;
        printf("We have %i processes.\n", num_procs);

        /* Send messages to all other processes */
        for (other_rank = 1; other_rank < num_procs; other_rank++)
        {
            sprintf(buf, "Hello %i!", other_rank);
            MPI_Send(buf, sizeof(buf), MPI_CHAR, other_rank,
                     0, MPI_COMM_WORLD);
        }

        /* Receive messages from all other process */
        for (other_rank = 1; other_rank < num_procs; other_rank++)
        {
            MPI_Recv(buf, sizeof(buf), MPI_CHAR, other_rank,
                     0, MPI_COMM_WORLD, MPI_STATUS_IGNORE);
            printf("%s\n", buf);
        }

    } else {

        /* Receive message from process #0 */
        MPI_Recv(buf, sizeof(buf), MPI_CHAR, 0,
                 0, MPI_COMM_WORLD, MPI_STATUS_IGNORE);
        assert(memcmp(buf, "Hello ", 6) == 0),

        /* Send message to process #0 */
        sprintf(buf, "Process %i reporting for duty.", my_rank);
        MPI_Send(buf, sizeof(buf), MPI_CHAR, 0,
                 0, MPI_COMM_WORLD);

    }

    /* Tear down the communication infrastructure */
    MPI_Finalize();
    return 0;
}

C++ Procedure

  1. Use Vim (vim wiki_mpi_example.c) to create your C++ source file.

  2. Save your file and return to the Bash shell.

  3. Load the MPI compiler using the openmpi module.

    module load openmpi

  4. Compile the C++ source into a binary executable file.

    mpicc wiki_mpi_example.c -o hello.mpi

  5. Use ls -al to verify the presence of the hello.mpi binary in your working directory.

Step 4: Run the Job

  1. Before proceeding, ensure that you are still in your working directory (using pwd) and that you still have the openmpi module loaded (using module list).

    • We need to be in the same path/directory as our sbatch script and our C++ binary. Use ls -al to confirm their presence.

  2. Use sbatch to schedule your batch job in the queue.

    sbatch slurm_mpi_example.job

    This command will automatically queue your job using slurm and produce a job number. You can check the status of your job at any time with the squeue command.

    squeue --job <jobnumber>

    You can also stop your job at any time with the scancel command.

    scancel --job <jobnumber>

  3. View your results. You can view the contents of these files using the less command followed by the file name. 

    less test_<jobnumber>.out

    Your output should look something like this:

    Currently Loaded Modules:
1) gnu/5.4.0   2) openmpi/1.10.7

We have 16 processes.
Process 1 reporting for duty.
Process 2 reporting for duty.
Process 3 reporting for duty.
Process 4 reporting for duty.
Process 5 reporting for duty.
Process 6 reporting for duty.
Process 7 reporting for duty.
Process 8 reporting for duty.
Process 9 reporting for duty.
Process 10 reporting for duty.
Process 11 reporting for duty.
Process 12 reporting for duty.
Process 13 reporting for duty.
Process 14 reporting for duty.
Process 15 reporting for duty.

  4. Download your results (using the scp command or an SFTP client) or move them to persistent storage. See our moving data section for help.

Additional Examples

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