Co-array Fortran on Niagara

Versions 12 and higher of the Intel Fortran compiler, and version 5.1 and up of the GNU Fortran compiler, support almost all of Co-array Fortran, and are installed on Niagara.

This page will briefly sketch how to compile and run Co-array Fortran programs using these compilers.

Example

Here is an example of a co-array fortran program:

program Hello_World
  integer :: i ! Local variable
  integer :: num[*] ! scalar coarray
  if (this_image() == 1) then
    write(*,'(a)') 'Enter a number: '
    read(*,'(i80)') num
    ! Distribute information to other images
    do i = 2, num_images()
      num[i] = num
    end do
  end if
  sync all ! Barrier to make sure the data has arrived
  ! I/O from all nodes
  write(*,'(a,i0,a,i0)') 'Hello ',num,' from image ', this_image()
end program Hello_world

(Adapted from [1]).

Compiling, linking and running co-array fortran programs is different depending on whether you will run the program only on a single node (with 8 cores), or on several nodes, and depends on which compiler you are using, Intel, or GNU.

Intel compiler instructions for Coarray Fortran

Loading necessary modules

First, you need to load the module for version 12 or greater of the Intel compilers, as well as Intel MPI.

module load NiaEnv/2019b  intel/2019u4 intelmpi/2019u4

There are two modes in which the intel compiler supports coarray fortran:

1. Single node usage

2. Multiple node usage

The way you compile and run for these two cases is different.

Note: For multiple node usage, it makes sense to have to load the IntelMPI module, since Intel's implementation of Co-array Fortran uses MPI. However, the Intel MPI module is needed even for single-node usage, just in order to link successfully.

Single node usage

Compilation

ifort -O3 -xHost -coarray=shared -c [sourcefile] -o [objectfile]

Linking

ifort -coarray=shared [objectfile] -o [executable]

Running

To run this co-array program on one node with 16 images (co-array version for what openmp calls a thread and mpi calls a process), you simply put

./[executable]

in your job submission script. The reason that this gives 16 images is that HyperThreading is enabled on Niagara nodes, which makes it seem to the system as if there are 80 computing units on a node, even though physically there are only 40.

To control the number of images, you can change the FOR_COARRAY_NUM_IMAGES environment variable:

export FOR_COARRAY_NUM_IMAGES=2
./[executable]

This can be useful for testing.

An example submission script would look as follows:

#!/bin/bash
# SLURM submission script for SciNet Niagara (Intel Coarray Fortran)
#
#SBATCH --nodes=1
#SBATCH --time=1:00:00
#SBATCH --cpus-per-task=40
#SBATCH --job-name test

# DIRECTORY TO RUN - $SLURM_SUBMIT_DIR is directory job was submitted from
cd $SLURM_SUBMIT_DIR

# LOAD MODULES THAT THE APPLICATION WAS COMPILED WITH
module load NiaEnv/2019b  intel/2019u4 intelmpi/2019u4

# RUN THE APPLICATION WITH 80 IMAGES
export FOR_COARRAY_NUM_IMAGES=80
./[executable]

Multiple nodes usage

Please read over the following link: [2] for the newer intel compilers

module load NiaEnv/2019b  intel/2019u4 intelmpi/2019u4

Compilation

ifort -O3 -xHost -coarray=distributed -c [sourcefile] -o [objectfile]

Linking

ifort -coarray=distributed [objectfile] -o [executable]

Running

Because distributed co-array fortran is based on MPI, we need to launch the mpi processes on different nodes.

An example submission script would look as follows:

#!/bin/bash
#
#SBATCH --nodes=4
#SBATCH --time=1:00:00
#SBATCH --ntasks-per-node=40
#SBATCH --job-name test

# DIRECTORY TO RUN - $SLURM_SUBMIT_DIR is directory job was submitted from
cd $SLURM_SUBMIT_DIR

# LOAD MODULES THAT THE APPLICATION WAS COMPILED WITH
module load NiaEnv/2019b  intel/2019u4 intelmpi/2019u4

export FOR_COARRAY_NUM_IMAGES=$SLURM_NTASKS

# EXECUTION export COMMAND;FOR_COARRAY_NUM_IMAGES = nodes*ntasks-per-node
 ./[executable]

You can provide a configuration file using the ifort '-corray-config-file=file.cfg` option that will allow you to provide your own MPI parameters including the number of tasks per host and the number of total tasks, ie. images.