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SPRNG: A scalable library for pseudorandom number generation

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Title SPRNG: A scalable library for pseudorandom number generation
 
Creator MASCAGNI, M
SRINIVASAN, A
 
Subject long-range correlations
monte-carlo
parallel computers
ising-model
simulations
sequences
algorithm
tests
algorithms
design
documentation
experimentation
performance
reliability
standardization
parallel random-number generators
random-number software
linear congruential generator
lagged-fibonacci generator
random-number tests
 
Description In this article Re present background, rationale, and a description of the Scalable Parallel Random Number Generators (SPRNG) library. We begin by presenting some methods for parallel pseudorandom number generation. We will focus on methods based on parameterization, meaning that we will not consider splitting methods such as the leap-frog or blocking methods. We describe, in detail, parameterized versions of the following pseudorandom number generators: (i) linear congruential generators, (ii) shift-register generators, and (iii) lagged-Fibonacci generators. We briefly describe the methods, detail some advantages and disadvantages of each method, and recount results from number theory that impact our understanding of their quality in parallel applications. SPRNG was designed around the uniform implementation of different families of parameterized random number generators. We then present a short description of SPRNG. The description contained within this document is meant only to outline the rationale behind and the capabilities of SPRNG. Much more information, including examples and detailed documentation aimed at helping users with putting and using SPRNG on scalable systems is available at http://sprng.cs.fsu.edu. In this description of SPRNG we discuss the random-number generator library as well as the suite of tests of randomness that is an integral Dart of SPRNG. Random-number tools for parallel Monte Carlo applications must be subjected to classical as well as new types of empirical tests of randomness to eliminate generators that show defects when used in scalable environments.
 
Publisher ASSOC COMPUTING MACHINERY
 
Date 2011-07-18T21:17:06Z
2011-12-26T12:50:50Z
2011-12-27T05:36:58Z
2011-07-18T21:17:06Z
2011-12-26T12:50:50Z
2011-12-27T05:36:58Z
2000
 
Type Article
 
Identifier ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 26(3), 436-461
0098-3500
http://dx.doi.org/10.1145/358407.358427
http://dspace.library.iitb.ac.in/xmlui/handle/10054/5070
http://hdl.handle.net/10054/5070
 
Language en