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matlabrandomparallel-processingparfor

MATLAB: How to set random seed in parfor to produce same results as serial for?


I set up the following minimal example:

rng(0);

randseedoffset = random('unid', 10^5) + 1;

t = cell(10,1);
for i = 1:10
    rng(randseedoffset+i);
    t{i} = random('unid', 1000);
end

disp(t);

This will generate 10 random numbers and store them in t. It will always produce the same random numbers reliably because I set the seed with rng in the for loop.

If I now change for to parfor, I get different results! Though they will also always be reproducible.

I want to accelerate my code with parfor and still obtain the same exact same random numbers as with for...


Solution

  • Ok, I just found the reason:

    MATLAB supports different random number genereation algorithms. While in the usual setting of the current version this is the Mersenne Twister. When you go into the parfor loop, this changes to what they call 'Combined Recursive Method'.

    The problem can be fixed by explicitely setting the type to 'twister' in the loop:

    parfor i = 1:10
        rng(randseedoffset+i, 'twister');
        t{i} = random('unid', 1000);
    end