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

12Citations
Citations of this article
19Readers
Mendeley users who have this article in their library.
Get full text

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. © 2012 Springer-Verlag.

Cite

CITATION STYLE

APA

Nandapalan, N., Brent, R. P., Murray, L. M., & Rendell, A. P. (2012). High-performance pseudo-random number generation on graphics processing units. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7203 LNCS, pp. 609–618). https://doi.org/10.1007/978-3-642-31464-3_62

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free