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If you need to submit one or more single core jobs, and are not encountering problems with the lack of specific toolbox licenses, then you might wish to submit your jobs directly with SLURM rather than going through the MATLAB parallel computing toolbox.

1. Build a MATLAB .m code file

Include all of the MATLAB commands that you need to execute in a MATLAB .m file, such as sample.m and place it somewhere in your home directory or subdirectory. The creation and contents of a .m file are beyond the scope of this document. Consult the MATLAB documentation for information on .m files.

2. Create a SLURM batch script

You will need to execute MATLAB from within a SLURM batch script, such as sample.slurm as follows. In this example, this file is saved in the same directory as sample.m.

sample.slurm

In this example the  sample.slurm  script calls  matlab  with the -r option followed by the MATLAB script name that was created in step #1. Leave off the trailing .m from the script name when calling MATLAB  this way.

Click here for more information about SLURM job scripts.

3. Submit the Job

After you have created sample.m and sample.SLURM, go to the directory where sample.SLURM resides, load the MATLAB module (if you have not already done so) and submit the job to the job scheduler:

You should now be able to see your job in the partition by going to your Linux terminal window and using the  squeue command.

This type of job submission will compete with all other jobs on the system for run time. If no processors are available then the job submission will wait in the partition until it is able to run.

Look at the list of MATLAB modules available. Different versions of MATLAB are available on respective clusters with some overlap.

Possible License Errors

This type of job may fail due to license checkout errors. MATLAB shares a site license with the rest of the campus. If your job is using a toolbox  for which there are no licenses available for checkout, the job will fail when it starts to run. You will need to use the parallel computing toolbox to avoid this problem.