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Argonne Leadership
Computing Facility

OpenMP

Overview

The OpenMP API is an open standard for parallel programming. The specification document can be found here: https://www.openmp.org. The specification describes directives, runtime routines, and environment variables that allow an application developer to express parallelism (e.g. shared memory multiprocessing and device offloading). Many compiler vendors provide implementations of the OpenMP specification (https://www.openmp.org/specifications).

Setting the environment to use OpenMP on Polaris

Many of the programming environments available on Polaris have OpenMP support.

module OpenMP CPU support? OpenMP GPU support?
PrgEnv-nvhpc yes yes
llvm yes yes
PrgEnv-gnu yes no
PrgEnv-cray yes yes*

*Currently PrgEnv-cray is not recommended for OpenMP offload.

By default, the PrgEnv-nvhpc module is loaded. To switch to other modules, you can use module switch.

Using PrgEnv-nvhpc

This is loaded by default, so there's no need to load additional modules. You can confirm that it is loaded by running module list to check that PrgEnv-nvhpc is in the list.

Using LLVM

To use the LLVM module, load the following.

module load mpiwrappers/cray-mpich-llvm
module load cudatoolkit-standalone

See the the LLVM compiling page here for more information.

Using PrgEnv-gnu

To switch from PrgEnv-nvhpc to PrgEnv-gnu you can run:

module switch PrgEnv-nvhpc PrgEnv-gnu

The gcc/gfortran on Polaris was not built with GPU support. To use OpenMP on the CPU, you need to unload craype-accel-nvidia80:

module unload craype-accel-nvidia80

Using PrgEnv-cray

To switch from PrgEnv-nvhpc to PrgEnv-cray you can run:

module switch PrgEnv-nvhpc PrgEnv-cray

To use OpenMP on the CPU only, also unload craype-accel-nvidia80:

module unload craype-accel-nvidia80

To use OpenMP on the GPU, load cudatoolkit-standalone, although this is not recommended at the moment.

module load cudatoolkit-standalone

Building on Polaris

The following table shows what compiler and flags to use with which PrgEnv:

module compiler flags
PrgEnv-nvhpc cc/CC/ftn (nvc/nvc++/nvfortran) -mp=gpu -gpu=cc80
llvm mpicc/mpicxx (clang/clang++) -fopenmp -fopenmp-targets=nvptx64-nvidia-cuda
PrgEnv-gnu cc/CC/ftn (gcc/g++/gfortran) -fopenmp
PrgEnv-cray cc/CC/ftn -fopenmp

For example to compile a simple code hello.cpp:

For PrgEnv-nvhpc, after loading the modules as discussed above we would use:

CC -mp=gpu -gpu=cc80 hello.cpp
ftn -mp=gpu -gpu=cc80 hello.F90

For LLVM, after loading the modules as discussed above:

mpicxx -fopenmp -fopenmp-targets=nvptx64-nvidia-cuda hello.cpp 

For PrgEnv-gnu, after loading the modules as discussed above we would use:

CC -fopenmp hello.cpp
ftn -fopenmp hello.F90

For PrgEnv-cray, after loading the modules as discussed above we would use:

CC -fopenmp hello.cpp
ftn -fopenmp hello.F90

Running on Polaris

To run, you can run the produced executable or with mpiexec in a job script, and then submit the script to the Polaris queue, like:

$ cat submit.sh
#!/bin/sh
#PBS -l select=1:system=polaris
#PBS -l walltime=0:30:00
#PBS -q debug 
#PBS -A Catalyst
#PBS -l filesystems=home:eagle

cd ${PBS_O_WORKDIR}
 mpiexec -n 1 ./executable
$ # submit to the queue:
$ qsub -l select=1:system=polaris -l walltime=0:30:00 -l filesystems=home:eagle -q debug -A Catalyst ./submit.sh

In the above, having the PBS options in the script and on the command line is redundant, but we put it there to show both ways of launching. This submits the script to one node in the debug queue on Polaris, requesting 30 min and the eagle and home filesystems. It will charge project Catalyst for the time.

More details for setting up the job script are in Job Scheduling and Execution section.

Example

$ cat hello.cpp
#include <stdio.h>
#include <omp.h>

int main( int argv, char** argc ) {

  printf( "Number of devices: %d\n", omp_get_num_devices() );

  #pragma omp target
  {
    if( !omp_is_initial_device() )
      printf( "Hello world from accelerator.\n" );
    else
      printf( "Hello world from host.\n" );
  }
  return 0;
}

$ cat hello.F90
program  main
  use omp_lib
  implicit none
  integer flag

  write(*,*) "Number of devices:", omp_get_num_devices()

  !$omp target map(from:flag)
    if( .not. omp_is_initial_device() ) then
      flag = 1
    else
      flag = 0
   endif
  !$omp end target

   if( flag == 1 ) then
      print *, "Hello world from accelerator"
   else
      print *, "Hello world from host"
   endif

 end program main

$ # To compile
$ CC -mp=gpu -gpu=cc80 hello.cpp -o c_test
$ ftn -mp=gpu -gpu=cc80 hello.F90 -o f_test

$ # To run 
$ mpiexec -n 1 ./c_test
Number of devices: 4
Hello world from accelerator.
$ mpiexec -n 1 ./f_test
 Number of devices:            4
 Hello world from accelerator