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Parallel MATLAB profile setup and batch submission.md

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Parallel MATLAB batch submission

Setting up the cluster profile

In order to submit a PBS script that takes advantage of MATLAB Parallel Server you first need to set up a new cluster profile specific to Wheeler. Thankfully this has already been done and all you need to do as a user is import the profile and that only needs to be done once. If you would like to do this interactively you can start an interactive session with the following:

wheeler-sn:~$ qsub -I -l walltime=01:00:00 -l nodes=1:ppn=8

Once you have a node allocated to you load the MATLAB module and start a MATLAB session:

wheeler001:~$ module load matlab/R2019a
wheeler001:~$ matlab -nodisplay

To get started, type doc.
For product information, visit www.mathworks.com.
>>

Now simply import the wheeler cluster profile availble in the root matlab folder:

>> parallel.importProfile('/opt/local/MATLAB/R2019a/wheeler.settings')

With the settings imported you can now launch parallel pools for computation using the wheeler cluster profile. The code below is an example to test parallel computing across two nodes on Wheeler while timing execution:

>> poolobj = parpool('wheeler', 16)
>> tic
>> n = 200
>> A = 500
>> a = zeros(1,n)
>> parfor i = 1:n
>> a(i) = max(abs(eig(rand(A))))
>> end
>> toc
>> delete(poolobj);

Even better is to do everything using a batch script and avoid the mistakes associated with interactive computing. Below is an example MATLAB script named parallel_matlab.m that will import our cluster profile and compare the time of computation for a sequential for loop and a parallel for loop with 16 cores ('workers' in MATLAB speak):

% If you have already set up your cluster profile you can comment or delete the following line
parallel.importProfile('/opt/local/MATLAB/R2019a/wheeler.settings')

poolobj = parpool('wheeler', 16);

tic
n = 200;
A = 500;
a = zeros(1,n);
for i 1:n;
    a(i) = max(abs(eig(rand(A))))
end
toc

tic
n = 200;
A = 500;
a = zeros(1,n);
parfor i 1:n;
    a(i) = max(abs(eig(rand(A))))
end
toc
delete(poolobj);

Now the PBS script we will call parallel_matlab.pbs to submit your sample MATLAB program:

#!/bin/bash

#PBS -N parallel_matlab
#PBS -l walltime=01:00:00
#PBS -l nodes=1:ppn=8
#PBS -j oe

cd #PBS_O_WORKDIR

module load matlab/R2019a

matlab -r -nodisplay parallel_matlab > parallel_matlab.out

Submit your PBS script with qsub parallel_matlab.pbs and hopefully all goes swimmingly. If you require assistance with MATLAB parallel computing please send an email to [email protected].