Parallel computing on a cluster
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I have a script test.m that includes parfor-loops.
In MATLAB 2014a on my personal computer it runs the parallel job perfectly.
On a huge Linux computer cluster it runs test.m perfectly if I have started MATLAB 2014a graphically through X on the frontend.
However, when submitting test.m to the queue it discards the parallelness and runs everything as in for-loops -- on a single core on the given node.
What I write:
>> submat -q q12 test.m
q12 is the queue name.
Anyone with a clue??
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Kevin Claytor
2014-7-7
This would probably be a question more suited for your cluster sysadmin. My guess is there's probably something in your queue submission file that is missing. Your cluster probably has a help page / wiki (for example, Duke's is: https://wiki.duke.edu/display/SCSC/DSCR ), I'd start there.
If you still can't find anything, we'll need some more details, for instance, what scheduler are you using? Is 'submat' a script or a command? If it's a script, can you post it?
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Shashank Prasanna
2014-7-7
My guess is that when you queue it, it launches MATLAB without Java. Java is required to use PCT. That also explains why it works fine when you X11 forward MATLAB. See below:
"The client session of MATLAB must be running the Java® Virtual Machine (JVM™) to use Parallel Computing Toolbox software."
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Shashank Prasanna
2014-7-8
you could alternatively consider "-nodesktop" which launches jvm but not the desktop.
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Thomas Ibbotson
2014-7-8
We would need to see the code for 'submat', but my guess is that an independent job is being created rather than a communicating job. If you want to run a script with parfor loops on a cluster you need a communicating 'pool' job. For example you can submit one with 'batch' like this:
myCluster = parcluster('myClusterProfile');
job = batch(myCluster, 'test', 'Pool', myCluster.NumWorkers - 1);
wait(job);
fetchOutputs(job);
The 'Pool' argument instructs batch to create a communicating 'pool' job using the given number of workers to create the pool. You need to have at least 1 spare worker to act as the 'client', which is why I subtracted 1 from the total number of workers that the cluster has.
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