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Date: Thu, 25 Apr 2013 17:01:58 -0700 (PDT)
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Subject: random numbers in parallel
From: Gideon <gideon.simpson@gmail.com>
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Xref: news.mathworks.com comp.soft-sys.matlab:794373

I was wondering if people knew how robust the standard matlab rng function was when used in parallel matlab.  The problem I have in mind just has a parfor loop and I'm generating monte carlo samples.  I know there are issues when using random numbers in parallel to ensure each thread is generating independent samples.  How is this handled in MATLAB?   If I generically set rng(SEED) at the beginning of my code, then go into the parallel section, calling randn, will that be sufficient, or do I need to do something more sophisticated?