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Techniques for Empirical Testing of Parallel Random Number Generators (1998)
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| Venue: | Proc. International Conference on Supercomputing (ICS'98 |
| Citations: | 3 - 0 self |
BibTeX
@INPROCEEDINGS{Coddington98techniquesfor,
author = {Paul D. Coddington and Sung-hoon Ko},
title = {Techniques for Empirical Testing of Parallel Random Number Generators},
booktitle = {Proc. International Conference on Supercomputing (ICS'98},
year = {1998}
}
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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. Current address. 1 Introduction Parallel computers are now commonly used for computatio...
Keyphrases
parallel random number generator empirical testing random number generator parallel computer current address parallel algorithm preliminary result many application computational science dimensional ising model monte carlo simulation several parallel random number generator little work introduction parallel computer sequential random number generator large-scale monte carlo simulation computational science application good randomness property exact result many program
