parallelization and mex-compiled code

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martin
martin on 6 Feb 2014
Commented: martin on 9 Feb 2014
I want to optimize a mex-compiled function (fortran-90 source) defined over an 1D interval by computing its values on a sufficiently fine sampling. It works fine with a for-loop but when I try parfor (for speed) I get crashes in the mex-compiled code (getting a error from one of the workers). Is this a documented problem, and does anyone have suggestions how to localize what goes wrong?
I run MatlabR2013a and Ubuntu 13.10 on a 16 core (32 virtual) machine and I get 12 workers when I do matlabpool.
  1 Comment
Matt J
Matt J on 6 Feb 2014
No, there is no general prohibition against using mex files with parfor. Show us the plain for-loop and the parfor version.

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Accepted Answer

Matt J
Matt J on 6 Feb 2014
Edited: Matt J on 6 Feb 2014
You should try running a plain for-loop first, but with the iterations in random order, i.e., instead of
for i=1:n
...
end
run as
for i=randperm(n)
...
end
This is a good way to test whether your code is independent of the order of the iterations (a basic requirement of parfor) before the Parallel Computing Toolbox even gets involved.
  5 Comments
Matt J
Matt J on 6 Feb 2014
Can you try it on a different machine to see if it's hardware problem? I don't see anything wrong with the code.
martin
martin on 9 Feb 2014
Thanks for your input, I will try another machine asap. Just an additional observation: The program crashes on the fortran90 statement "call mxCopyPtrToReal8(inptr_xdim,realxdim,1)" i.e a standardconstruction right out of the manualmapges for mex

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