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Argonne Leadership Computing Facility

OpenMP on Aurora


The OpenMP API is an open standard for parallel programming. The specification document can be found here: 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 (

Setting the environment to use OpenMP on Aurora

The Intel oneAPI Programming Environment is the main environment on Aurora to maximally use the hardware. oneAPI has OpenMP support for both CPU threads and GPU devices. The oneAPI module is loaded by default in your environment:

> module list

Currently Loaded Modules:
  1) gcc/11.2.0                    3) intel_compute_runtime/release/agama-devel-551   5) libfabric/   7) cray-libpals/1.3.3
  2) mpich/51.2/icc-all-pmix-gpu   4) *oneapi/eng-compiler/2022.12.30.003*              6) cray-pals/1.3.3

However, additional versions of oneAPI with newer compiler versions can be found by adding additional modules to your path:

> module use /soft/modulefiles/
> module avail oneapi

-------------------------------------------------------------------------------- /soft/modulefiles ---------------------------------------------------------------------------------\
   oneapi/eng-compiler/2023.05.15.003    oneapi/eng-compiler/2023.10.15.002        oneapi/release/2023.10.15.001        spack-pe-oneapi/0.5-rc1 (D)
   oneapi/eng-compiler/2023.05.15.006    oneapi/eng-compiler/2023.12.15.002 (D)    oneapi/release/2023.12.15.001 (D)
   oneapi/eng-compiler/2023.05.15.007    oneapi/release/2023.05.15.001             spack-pe-oneapi/0.4-rc1

------------------------------------------------------------------------- /opt/aurora/23.073.0/modulefiles -------------------------------------------------------------------------\
   oneapi/eng-compiler/2022.12.30.003 (L)    oneapi/release/2022.12.30.001
The additional oneAPI modules can be loaded with module load oneapi/eng-compiler/2023.10.15.002, for example.

Building on Aurora

The following table shows the compiler and flags

language MPI wrapper compiler (underlying compiler) flag to turn on OpenMP support and target CPU threads additional flags to target GPU devices
Fortran mpifort (ifx) -fiopenmp -fopenmp-targets=spir64_gen -Xopenmp-target-backend "-device pvc"
C mpicc (icx) -fiopenmp -fopenmp-targets=spir64_gen -Xopenmp-target-backend "-device pvc"
C++ mpicxx (icpx) -fiopenmp -fopenmp-targets=spir64_gen -Xopenmp-target-backend "-device pvc"

Running on Aurora

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

$ cat
#PBS -l select=1
#PBS -l walltime=0:30:00
#PBS -q EarlyAppAccess 
#PBS -A Project

 mpiexec -n 1 ./executable
$ # submit to the queue:
$ qsub -l select=1 -l walltime=0:30:00 -q EarlyAppAccess -A Project ./

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 EarlyAppAccess queue on Aurora, requesting 30 min. It will charge project Project for the time. You should replace it with your project name.

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


$ 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" );
      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()

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

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

 end program main

To compile

$ mpicxx -fiopenmp -fopenmp-targets=spir64_gen -Xopenmp-target-backend "-device pvc" hello.cpp -o c_test
$ mpifort -fiopenmp -fopenmp-targets=spir64_gen -Xopenmp-target-backend "-device pvc" hello.F90 -o f_test

To run

$ mpiexec -n 1 ./c_test
Number of devices: 6
Hello world from accelerator.
$ mpiexec -n 1 ./f_test
 Number of devices:            6
 Hello world from accelerator