High-performance pseudo-random number generation on graphics processing units

Authors:
Nimalan Nandapalan;Richard P. Brent;Lawrence M. Murray;Alistair P. Rendell
Affiliations:
Research School of Computer Science, The Australian National University, Australia;Research School of Computer Science, The Australian National University, Australia, Mathematical Sciences Institute, The Australian National University, Australia;CSIRO Mathematics, Informatics and Statistics, Australia;Research School of Computer Science, The Australian National University, Australia
Venue:
PPAM'11 Proceedings of the 9th international conference on Parallel Processing and Applied Mathematics - Volume Part I
Year:
2011

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Abstract

This work considers the deployment of pseudo-random number generators (PRNGs) on graphics processing units (GPUs), developing an approach based on the xorgens generator to rapidly produce pseudo-random numbers of high statistical quality. The chosen algorithm has configurable state size and period, making it ideal for tuning to the GPU architecture. We present a comparison of both speed and statistical quality with other common GPU-based PRNGs, demonstrating favourable performance of the xorgens-based approach.