DHPC Technical Report DHPC-025
Techniques for Empirical Testing of Parallel Random Number Generators
Paul D. Coddington and Sung-Hoon Ko
Archived: 19 January 1998
Published in Proc. of the ACM International Conference on
Supercomputing (ICS'98), Melbourne, July 1998.
Abstract
Parallel computers are now commonly used for computational science and
engineering, and many applications in these areas use random number
generators. For some applications, such as large-scale Monte Carlo
simulations, it is crucial that the random number generator have good
randomness properties.
Many programs are available for testing the quality of sequential
random number generators, but very little work has been done on
testing parallel random number generators.
We present some techniques for empirical testing of
random number generators on parallel computers, using tests
based on computational science applications as examples.
In particular, we focus on tests based on parallel algorithms
developed for Monte Carlo simulations of the two dimensional
Ising model, for which exact results are known.
Preliminary results of these tests are presented for several
parallel random number generators.
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