Naive parallel implementation of Mersenne Twister random numbergenerator

Discussion in 'C Programming' started by mjm2114@columbia.edu, Jun 4, 2008.

  1. Guest

    Hi there,

    I have a question on a naive implementation of a parallel MT that I've
    done using the fortran version of MT19937ar.f posted in Prof.
    Matsumoto's website. (http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/
    MT2002/emt19937ar.html)

    First, I setup a KISS RNG (Marsaglia, 1999)
    in the master node and seed it. I then use the first 4 outputs from
    the master node to
    seed the MT in the first worker node
    using subroutine init_by_array. I continue in the
    same manner for all subsequent worker nodes, taking the next 4
    outputs from the master node and using them to seed the MT in all
    worker nodes. Once this is done, I have a different MT ready for use
    in all the worker nodes. Do you think this is a good approach? I know
    that the seeds used to set up each worker node MTs
    have some correlation (since they are produced by the
    same KISS RNG), but given the gigantic
    period of the MT algorithm and the fact that KISS and MT are so
    different,
    wouldn't these correlations be insignificant
    for all practical purposes?

    I know I can't expect perfectly uncorrelated streams of outputs in
    each node as in serious parallel PRNGs (i.e. SPRNG), but I'm only
    going to use the code for small workstations/clusters of 8-16 nodes
    (using mpi). Any ideas on the max number of uncorrelated streams I can
    expect?

    Thanks

    Manuel
    , Jun 4, 2008
    #1
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