Robin-hpc

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(Matlab R2019b)
(Access)
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== Access ==
== Access ==
-
Todo: vegardds
+
Apply for access using this link: https://nettskjema.no/a/robin-hpc
== SLURM ==
== SLURM ==

Versjonen fra 22. feb 2021 kl. 09:36

Innhold

Hardware

Todo: vegardds

CPU and RAM

Storage

Access

Apply for access using this link: https://nettskjema.no/a/robin-hpc

SLURM

Todo: emmaste

Software

Matlab R2019b

Todo: sebastto

Setting up the SLURM job script

#SBATCH --job-name=matlab_job
#SBATCH --ntasks=1
#SBATCH --cpus-per-task 16

srun matlab -batch "addpath(genpath('/path/to/your/matlab/folder'));run('myScript.m')"

Running Matlab in batch mode is the most safe option for running MATLAB on a HPC. (From Mathworks documentation)[1]:

-batch statement

  • Starts without the desktop

  • Does not display the splash screen

  • Executes statement

  • Disables changes to preferences

  • Disables toolbox caching

  • Logs text to stdout and stderr

  • Does not display modal dialog boxes

  • Exits automatically with exit code 0 if script executes successfully. Otherwise, MATLAB terminates with a non-zero exit code.

The addpath(genpath('/path/to/your/matlab/folder')) part adds all files in the specified directory to the MATLAB search path. Afterwards we run the main script of your program with run('myScript.m').

Utilizing parallel computing in your MATLAB Script

When the SLURM worker node is setting up your job, a number of environment variables is set. We can use the environment variable SLURM_CPUS_ON_NODE to get the number of CPU cores available in our MATLAB script. In fact, we can use that variable to dynamically select the number of workers in the MATLAB parallel pool, so that your script works both on your own computer and on the HPC.

SLURM_CPUS_STR = getenv('SLURM_CPUS_ON_NODE');

% Delete parallel pool from earlier runs
delete(gcp('nocreate'));

if isempty(SLURM_CPUS_STR) 
    % Run on personal computer (with however many cores your CPU has)
    parpool(6);
else
    % Run on SLURM-scheduled HPC
    SLURM_CPUS_NUM = str2num(SLURM_CPUS_STR);
    parpool(SLURM_CPUS_NUM);
end

Anaconda

Todo: emmaste

Podman

alias docker=podman
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