OpenMP parallel jobs

OpenMP is a set of compiler directives, library routines and environment variables that can be used to specify shared-memory parallelism in C, C++ and Fortran codes.

OpenMP compiler directives can be inserted into source code to indicate to the compiler which sections of code can be readily parallelised, allowing a programmer to highlight the core sections of code that can benefit from OpenMP’s automated parallelisation. When compiled with a special compiler flag, the compiler will create a multi-threaded version of the application that can automatically distribute the annotated sections of code across multiple CPUs on the same compute node.

It should be stressed that not all codes will benefit from such attempts at parallelism, and not all sections of parallel code scale well to high CPU/thread counts. Users should test serial and parallel versions of their code to ensure that the parallel version is making good use of the additional processors.

Programming and Compiling with OpenMP

A detailed explanation of the OpenMP compiler directives can found in the guides for both the PGI and Intel compiler suites (see helpful links under the Additional advice section for more information).

  • To compile OpenMP code using the Intel compiler, compile with your normal set of Intel compiler flags, and add the -openmp argument.

  • To compile OpenMP code using the PGI compiler, compile with your normal set of PGI compiler flags, and add the compiler argument -mp

  • To compile OpenMP code using the GNU compilers, compile with your normal set of GNU compiler flags and add the compiler argment -fopenmp

Make sure that the correct module for your preferred compiler suite has already been added to your environment.

Submitting OpenMP jobs

The following job template will run an 8-core version of a program named omptest compiled with an Intel compiler:


#SBATCH -p parallel
#SBATCH --cpus-per-task=8
#SBATCH --mem=4000M

source /etc/profile
module add intel/21.0u4


The number of cores/threads required is specified in the --cpus-per-task option in the job script.

Note that a memory resource request is required for OpenMP jobs - as the job is unlikely to use all cores on a single compute node, the job scheduler needs to know what memory to reserve for this job to enable it to schedule other jobs with their own memory resource requests on the same node. If no memory resource request is specified, the default value of 500M is applied to the job.

OpenMP applications automatically set their number of threads based upon the value of the environment variable OMP_NUM_THREADS. For OpenMP jobs using the template above, the scheduler will automatically set this environment variable to match the CPUs requested in the --cpus-per-task option in the job script.