Employing AVX vectorization to improve the performance of random number generators View Full Text


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Article Info

DATE

2017-05

AUTHORS

L. Yu. Barash, M. S. Guskova, L. N. Shchur

ABSTRACT

By the example of the RNGAVXLIB random number generator library, this paper considers some approaches to employing AVX vectorization for calculation speedup. The RNGAVXLIB library contains AVX implementations of modern generators and the routines allowing one to initialize up to 1019 independent random number streams. The AVX implementations yield exactly the same pseudorandom sequences as the original algorithms do, while being up to 40 times faster than the ANSI C implementations. More... »

PAGES

145-160

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1134/s0361768817030033

DOI

http://dx.doi.org/10.1134/s0361768817030033

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1085593637


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