Employing AVX vectorization to improve the performance of random number generators


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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.

Sobre autores

L. Barash

Landau Institute for Theoretical Physics; Science Center in Chernogolovka

Autor responsável pela correspondência
Email: barash@itp.ac.ru
Rússia, Chernogolovka, 142432; Chernogolovka, 142432

M. Guskova

Science Center in Chernogolovka; National Research University Higher School of Economics

Email: barash@itp.ac.ru
Rússia, Chernogolovka, 142432; Moscow, 101000

L. Shchur

Landau Institute for Theoretical Physics; Science Center in Chernogolovka; National Research University Higher School of Economics

Email: barash@itp.ac.ru
Rússia, Chernogolovka, 142432; Chernogolovka, 142432; Moscow, 101000

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