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

Nimalan Nandapalan; Richard P. Brent; Lawrence M. Murray; Alistair P. Rendell

doi:10.1007/978-3-642-31464-3_62

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

Nimalan Nandapalan^*, Richard P. Brent, Lawrence M. Murray, Alistair P. Rendell

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Citations (Scopus)

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.

Original language	English
Title of host publication	Parallel Processing and Applied Mathematics - 9th International Conference, PPAM 2011, Revised Selected Papers
Pages	609-618
Number of pages	10
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-31464-3_62
Publication status	Published - 2012
Event	9th International Conference on Parallel Processing and Applied Mathematics, PPAM 2011 - Torun, Poland Duration: 11 Sept 2011 → 14 Sept 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	7203 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	9th International Conference on Parallel Processing and Applied Mathematics, PPAM 2011
Country/Territory	Poland
City	Torun
Period	11/09/11 → 14/09/11

Access to Document

10.1007/978-3-642-31464-3_62

Cite this

Nandapalan, N., Brent, R. P., Murray, L. M., & Rendell, A. P. (2012). High-performance pseudo-random number generation on graphics processing units. In Parallel Processing and Applied Mathematics - 9th International Conference, PPAM 2011, Revised Selected Papers (PART 1 ed., pp. 609-618). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7203 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-31464-3_62

Nandapalan, Nimalan ; Brent, Richard P. ; Murray, Lawrence M. et al. / High-performance pseudo-random number generation on graphics processing units. Parallel Processing and Applied Mathematics - 9th International Conference, PPAM 2011, Revised Selected Papers. PART 1. ed. 2012. pp. 609-618 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

@inproceedings{016742d056434dc8af21c2535d3407c8,

title = "High-performance pseudo-random number generation on graphics processing units",

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.",

keywords = "Monte Carlo, Pseudo-random number generation, graphics processing units",

author = "Nimalan Nandapalan and Brent, {Richard P.} and Murray, {Lawrence M.} and Rendell, {Alistair P.}",

year = "2012",

doi = "10.1007/978-3-642-31464-3_62",

language = "English",

isbn = "9783642314636",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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pages = "609--618",

booktitle = "Parallel Processing and Applied Mathematics - 9th International Conference, PPAM 2011, Revised Selected Papers",

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note = "9th International Conference on Parallel Processing and Applied Mathematics, PPAM 2011 ; Conference date: 11-09-2011 Through 14-09-2011",

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Nandapalan, N, Brent, RP, Murray, LM & Rendell, AP 2012, High-performance pseudo-random number generation on graphics processing units. in Parallel Processing and Applied Mathematics - 9th International Conference, PPAM 2011, Revised Selected Papers. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 7203 LNCS, pp. 609-618, 9th International Conference on Parallel Processing and Applied Mathematics, PPAM 2011, Torun, Poland, 11/09/11. https://doi.org/10.1007/978-3-642-31464-3_62

High-performance pseudo-random number generation on graphics processing units. / Nandapalan, Nimalan; Brent, Richard P.; Murray, Lawrence M. et al.
Parallel Processing and Applied Mathematics - 9th International Conference, PPAM 2011, Revised Selected Papers. PART 1. ed. 2012. p. 609-618 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7203 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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

Y1 - 2012

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 - Monte Carlo

KW - Pseudo-random number generation

KW - graphics processing units

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U2 - 10.1007/978-3-642-31464-3_62

DO - 10.1007/978-3-642-31464-3_62

M3 - Conference contribution

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 -

Nandapalan N, Brent RP, Murray LM, Rendell AP. High-performance pseudo-random number generation on graphics processing units. In Parallel Processing and Applied Mathematics - 9th International Conference, PPAM 2011, Revised Selected Papers. PART 1 ed. 2012. p. 609-618. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-31464-3_62

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

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