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Gaussian random number generators

delete2007-11-02
delete141
PRE
AI
D
David B. Thomas *
W
Wayne Luk
P
Philip H. W. Leong
J
John Villasenor
DOI：10.1145/1287620.1287622delete
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Abstract

Abstract

En 中文
Rapid generation of high quality Gaussian random numbers is a key capability for simulations across a wide range of disciplines. Advances in computing have brought the power to conduct simulations with very large numbers of random numbers and with it, the challenge of meeting increasingly stringent requirements on the quality of Gaussian random number generators (GRNG). This article describes the algorithms underlying various GRNGs, compares their computational requirements, and examines the quality of the random numbers with emphasis on the behaviour in the tail region of the Gaussian probability density function.
Keywords:
random numbers
Gaussian
normal
simulation
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Journal

ACM Computing Surveys cover
ACM Computing Surveys
IF:
28
Papers:
2.4K
Citations:
3.5W

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