Run one of the commands below, which will list available versions and the corresponding module files:
module spider matlab
Load the appropriate module file. For example, to run version R2014a:
module load MATLAB/2014a
The module load command sets up your environment, including the PATH to find the proper version of the MATLAB program.
The MATLAB program is too large to fit on a login node. If you try to run it there, it will crash. Instead, launch it in an interactive or batch job (see below).
To launch MATLAB, using
# launch the MATLAB GUI matlab # or launch the MATLAB command line prompt maltab -nodisplay # or to launch a script matlab -nodisplay < runscript.m
To run Matlab interactively, you need to create an interactive session on a compute node.
You could start an interactive session using 4 cores on 1 node using something like
srun --pty --x11 -c 4 -p interactive -t 4:00:00 bash
Once your interactive session starts, you can load the appropriate module file and start Matlab as described above.
See our Slurm documentation for more detailed information on requesting resources for interactive jobs.
Batch Mode (without a GUI)
Create a batch script containing both instructions to the scheduler and shell instructions to set up directories and start Matlab. At the point you wish to start Matlab, use a command like:
matlab -nodisplay -nosplash -r YourFunction < /dev/null
This command will run the contents of YourFunction.m. Your batch submission script must either be in or
cd to the directory containing YourFunction.m for this to work.
Below is a sample batch script to run Matlab in batch mode on Grace. If the name of the script is runit.sh, you would submit it using
Here's a script for Grace:
#!/bin/bash #SBATCH -J myjob #SBATCH -c 4 #SBATCH -t 24:00:00 #SBATCH -p day module load MATLAB/2016b matlab -nodisplay -nosplash -r YourFunction < /dev/null
Unless you specify otherwise (using > redirects), both output and error logs will show up in the slurm-jobid.out log file in the same directory as your submission script.
Using More than 12 Cores with Matlab
In Matlab, 12 workers is a poorly documented default limit (seemingly for historical reasons) when setting up the parallel environment. You can override it by explicitly setting up your parpool before calling parfor or other parallel functions.