HPC High Performance Computing: 12. Example Scripts


In this section, we provide you a set of examples which will be useful to you to configure scripts depending on your research needs. If you are interested in taking a look at them, they are all available in /soft/slurm_templates directory, which is only accessible in calculation nodes. In order to run the scripts, copy them to your homedtic folder.

cocana@node001:~$ ls -l /soft/slurm_templates/
total 8
-rw-r--r-- 1 root root  579 Apr  5 12:06 01-single_core_job.sh
-rw-r--r-- 1 root root  691 Apr  5 12:15 02-multicore-intel_job.sh
-rw-r--r-- 1 root root  664 Apr  5 12:19 03-multiprocessor-intel_job.sh
-rw-r--r-- 1 root root 1097 Apr  5 12:25 04-mpi_job.sh
-rw-r--r-- 1 root root  918 Apr  5 12:42 05-hybrid_openmp_mpi_job.sh
-rw-r--r-- 1 root root  519 Apr  5 13:16 06-array_job.sh
-rw-r--r-- 1 root root  774 Apr  5 13:42 07-gpu_job.sh
drwxr-xr-x 3 root root   14 Apr  5 13:22 bin
drwxr-xr-x 2 root root    0 Apr  5 13:45 output_examples

Single and Multi-core Jobs

Depending on resources consumption, the simulation could need more than one processor. In the bash script, it is possible to specify how many cores are requested to run the job. If the simulation uses more than one core, you have to add --cpu-per-task or -c parameter with the number of CPU cores used per task. Without this option, the controller will allocate one core. Remember to specify the tasks number with --ntasks or -n parameter.

Single core


#SBATCH --ntasks=X where X => 1              

#SBATCH --ntasks=X where X => 1

#SBATCH --cpus-per-task=Y where Y > 1


In some cases, you will maybe need to run your job either on an AMD or Intel architecture. This feature can be selected by --constraint or -C parameter.

For more information, see 01-single_core_job.sh and 02-multicore-intel.job.sh files.

OMP, MPI and Hybrid Jobs

It is possible to find different types of parallelism: OpenMP, OpenMPI or a hybrid solution combining both of them. On one hand, you will use OpenMP for parallelism within a multi-core node. Since it is a multithreading implementation, an OMP_NUM_THREADS variable has to be defined. On the other hand, if the parallelism is between nodes, you will use OpenMPI. So, in our sbatch script, it will be necessary to specify the number of nodes, the number tasks on each node and each CPU and finally, with --distribution=cyclic:cyclic parameter, the tasks are distributed in a round-robin fashion. It is essential to load the OpenMPI module.


OpenMPI Hybrid

#SBATCH --cpus-per-tasks=X where X > 1

export OMP_NUM_THREADS=X where X > 1

#SBATCH --ntasks=X where X => 1

#SBATCH --cpus-per-task=Y where Y > 1

#SBATCH --nodes=Z where Z =>2

#SBATCH --ntasks-per-node=W where W > 1

#SBATCH --ntasks-per-socket=U where U > 1

#SBATCH --distribution=cyclic:cyclic

module load OpenMPI/4.1.2-GCC-10.2.0

Combine both options

For more information, see 03-multiprocessor-intel_job.sh, 04-mpi_job.sh and hybrid_openmp_mpi_job.sh files.

Array Jobs

Using an array, you are able to execute multiple jobs with the same parameters. In your sbatch script, you have to specify the --array option.


#SBATCH --array=1-X where X > 1

For more information, see 06-array_job.sh file.

GPU Jobs

It is essential to use --gres parameter to reserve a GPU resource and load the CUDA module.


#SBATCH --gres=gpu:1

module load CUDA/11.4.3

For more information, see 07-gpu_job.sh file.


Here, there is the official web page with all available sbatch parameters: https://slurm.schedmd.com/sbatch.html