Parallel random numbers as easy as 1, 2, 3

Most pseudorandom number generators (PRNGs) scale poorly to massively parallel high-performance computation because they are designed as sequentially dependent state transformations. We demonstrate that independent, keyed transformations of counters produce a large alternative class of PRNGs with ex...

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Bibliographic Details
Published in:	2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC) pp. 1 - 12
Main Authors:	Salmon, John K., Moraes, Mark A., Dror, Ron O., Shaw, David E.
Format:	Conference Proceeding
Language:	English
Published:	New York, NY, USA ACM 12.11.2011 IEEE
Series:	ACM Conferences
Subjects:	Batteries Computer systems organization > Dependable and fault-tolerant systems and networks Cryptography General and reference > Cross-computing tools and techniques > Performance Generators Hardware Mathematics of computing > Probability and statistics > Probabilistic reasoning algorithms > Random number generation Memory management Networks > Network performance evaluation Radiation detectors Testing Theory of computation > Models of computation > Concurrency Theory of computation > Models of computation > Concurrency > Parallel computing models
ISBN:	145030771X, 9781450307710
ISSN:	2167-4329
Online Access:	Get full text
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