Efficient reversible uniform and non-uniform random number generation in UNU.RAN

Srikanth B. Yoginath; Kalyan S. Perumalla

Efficient reversible uniform and non-uniform random number generation in UNU.RAN

Srikanth B. Yoginath, Kalyan S. Perumalla

Systems and Decision Sciences

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

1 Scopus citations

Abstract

Reversible random number generations are useful in large-scale fault-tolerant parallel computations and parallel discrete event simulations that are based on reversible computation. The Universal Non-Uniform Random Number Generator (UNU.RAN) is one of the popular random number generators used in the simulation community, but the generators are forward-only in nature. In this paper, we develop new reverse algorithm for the default uniform random number generator algorithm of UNU.RAN and also a few nonuniform random generators that use the Transform Density Reduction (TDR) method. We verify the correctness of reversals of our algorithms and also provide performance results to demonstrate reverse computing runtime adds little overheads relative to its forward counterpart.

Original language	English
Title of host publication	Simulation Series
Editors	Erika Frydenlund, Shafagh Shafer, Hamdi Kavak
Publisher	The Society for Modeling and Simulation International
Pages	13-22
Number of pages	10
Edition	2
ISBN (Electronic)	9781510860148
ISBN (Print)	9781510860131, 9781510860148, 9781510860155, 9781510860162, 9781510860179, 9781510860186, 9781510860186, 9781510860209
State	Published - 2018
Event	51st Annual Simulation Symposium, ANSS 2018, Part of the 2018 Spring Simulation Multi-Conference, SpringSim 2018 - Baltimore, United States Duration: Apr 15 2018 → Apr 18 2018

Publication series

Name	Simulation Series
Number	2
Volume	50
ISSN (Print)	0735-9276

Conference

Conference	51st Annual Simulation Symposium, ANSS 2018, Part of the 2018 Spring Simulation Multi-Conference, SpringSim 2018
Country/Territory	United States
City	Baltimore
Period	04/15/18 → 04/18/18

Funding

This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Keywords

Reverse random number generator
Reverse-computing

Cite this

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title = "Efficient reversible uniform and non-uniform random number generation in UNU.RAN",

abstract = "Reversible random number generations are useful in large-scale fault-tolerant parallel computations and parallel discrete event simulations that are based on reversible computation. The Universal Non-Uniform Random Number Generator (UNU.RAN) is one of the popular random number generators used in the simulation community, but the generators are forward-only in nature. In this paper, we develop new reverse algorithm for the default uniform random number generator algorithm of UNU.RAN and also a few nonuniform random generators that use the Transform Density Reduction (TDR) method. We verify the correctness of reversals of our algorithms and also provide performance results to demonstrate reverse computing runtime adds little overheads relative to its forward counterpart.",

keywords = "Reverse random number generator, Reverse-computing",

author = "Yoginath, {Srikanth B.} and Perumalla, {Kalyan S.}",

note = "Publisher Copyright: {\textcopyright} 2018 Society for Modeling & Simulation International (SCS).; 51st Annual Simulation Symposium, ANSS 2018, Part of the 2018 Spring Simulation Multi-Conference, SpringSim 2018 ; Conference date: 15-04-2018 Through 18-04-2018",

year = "2018",

language = "English",

isbn = "9781510860131",

series = "Simulation Series",

publisher = "The Society for Modeling and Simulation International",

number = "2",

pages = "13--22",

editor = "Erika Frydenlund and Shafagh Shafer and Hamdi Kavak",

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Yoginath, SB & Perumalla, KS 2018, Efficient reversible uniform and non-uniform random number generation in UNU.RAN. in E Frydenlund, S Shafer & H Kavak (eds), Simulation Series. 2 edn, Simulation Series, no. 2, vol. 50, The Society for Modeling and Simulation International, pp. 13-22, 51st Annual Simulation Symposium, ANSS 2018, Part of the 2018 Spring Simulation Multi-Conference, SpringSim 2018, Baltimore, United States, 04/15/18.

Efficient reversible uniform and non-uniform random number generation in UNU.RAN. / Yoginath, Srikanth B.; Perumalla, Kalyan S.
Simulation Series. ed. / Erika Frydenlund; Shafagh Shafer; Hamdi Kavak. 2. ed. The Society for Modeling and Simulation International, 2018. p. 13-22 (Simulation Series; Vol. 50, No. 2).

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

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N2 - Reversible random number generations are useful in large-scale fault-tolerant parallel computations and parallel discrete event simulations that are based on reversible computation. The Universal Non-Uniform Random Number Generator (UNU.RAN) is one of the popular random number generators used in the simulation community, but the generators are forward-only in nature. In this paper, we develop new reverse algorithm for the default uniform random number generator algorithm of UNU.RAN and also a few nonuniform random generators that use the Transform Density Reduction (TDR) method. We verify the correctness of reversals of our algorithms and also provide performance results to demonstrate reverse computing runtime adds little overheads relative to its forward counterpart.

AB - Reversible random number generations are useful in large-scale fault-tolerant parallel computations and parallel discrete event simulations that are based on reversible computation. The Universal Non-Uniform Random Number Generator (UNU.RAN) is one of the popular random number generators used in the simulation community, but the generators are forward-only in nature. In this paper, we develop new reverse algorithm for the default uniform random number generator algorithm of UNU.RAN and also a few nonuniform random generators that use the Transform Density Reduction (TDR) method. We verify the correctness of reversals of our algorithms and also provide performance results to demonstrate reverse computing runtime adds little overheads relative to its forward counterpart.

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KW - Reverse-computing

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Efficient reversible uniform and non-uniform random number generation in UNU.RAN

Abstract

Publication series

Conference

Funding

Keywords

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Cite this