TY - GEN
T1 - High-performance pseudo-random number generation on graphics processing units
AU - Nandapalan, Nimalan
AU - Brent, Richard P.
AU - Murray, Lawrence M.
AU - Rendell, Alistair P.
PY - 2012/8/27
Y1 - 2012/8/27
N2 - 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.
AB - 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.
KW - graphics processing units
KW - Monte Carlo
KW - Pseudo-random number generation
UR - http://www.scopus.com/inward/record.url?scp=84865244231&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-31464-3_62
DO - 10.1007/978-3-642-31464-3_62
M3 - Conference contribution
AN - SCOPUS:84865244231
SN - 9783642314636
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 609
EP - 618
BT - Parallel Processing and Applied Mathematics - 9th International Conference, PPAM 2011, Revised Selected Papers
T2 - 9th International Conference on Parallel Processing and Applied Mathematics, PPAM 2011
Y2 - 11 September 2011 through 14 September 2011
ER -