Page History

...

In order to utilise multi-cores within a single compute node, typically, the minimum programming effort would be the revision of the for loops into parfor loops in the .m file. For example, to parallelise the matlab jobs with the majority computation in a for loop read as

% Initialisation
A = 512;
N = 1024;
y = NaN(1,N);

% Executing serial `for` loop
for i = 1:N
  y(i) = max(abs(eig(rand(A))))
end

% Print results
disp(y);
disp("Done");

simply do 

% Initialisation
numberOfWorkers =8 48;
A = 512;
N = 1024;
y = NaN(1,N);

localCluster% Parallel =pool parclustercreation
parpool('local', numberOfWorkers);
localCluster.NumWorkers = numberOfWorkers;
parpool(localCluster);

parfor (i=
% Executing parallel `for` loop
parfor(i = 1:N, numberOfWorkers)
  y(i) = max(abs(eig(rand(A))))
end

% Print results
disp(y);
disp("Done");

For further explorations of the functionality provided by the Parallel Computing Toolbox, please refer to Mathworks website [https://au.mathworks.com/help/distcomp/index.html].  If you want to run Matlab jobs across more than one compute nodes and confirm that you get access to the feature Distributed Computing Server, please contact help@nci.org.au for further instructions.

...

#!/bin/bash

#PBS -q normal
#PBS -l walltime=02:00:00
#PBS -l ncpus=48
#PBS -l mem=190GB
#PBS -l jobfs=400GB
#PBS -l software=matlab_<institution>
#PBS -l wd

module load matlab/R2019b
module load matlab_licence/<institution>

# Must include `#PBS -l storage=scratch/ab12+gdata/yz98` if the job
# needs access to `/scratch/ab12/` and `/g/data/yz98/`. Details on
# https://opus.nci.org.au/display/Help/PBS+Directives+Explained.

matlab -nodisplay -nosplash -r "outputDir='$PBS_JOBFS',numberOfWorkers=$PBS_NCPUS, mfile, exitquit" > $PBS_JOBID.log

Please note, the flag -nodisplay passed to matlab enables running without the GUI, while the flag -nosplash disables the display of the Matlab logo.

...