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Pseudorandom Numbers Generation for Monte Carlo Simulations on GPUs: OpenCL Approach

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Numerical Computations with GPUs

Abstract

General principles of pseudorandom numbers production for Monte Carlo simulations on GPUs are discussed by creating an OpenCL open-source library of pseudorandom number generators PRNGCL. The library contains implementation of a number of the most popular uniform generators. The most popular pseudorandom number generators for Monte Carlo simulations and libraries for GPUs are reviewed. Some tricks for generators implementation on GPUs with OpenCL framework are considered. The performance results of implemented generators on several AMD and NVIDIA GPUs are presented.

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Acknowledgements

Author thanks to my colleagues and friends Alexey Strelchenko for providing benchmarks for PRNGCL library on high-end NVIDIA GPUs, Natalia Kolomoyets, Alexey Gulov and Yevgen Syetov for essential help with the text preparation.

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  1. Dnipropetrovsk National University, Dnipropetrovsk, Ukraine

    Vadim Demchik

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  1. Vadim Demchik
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Correspondence to Vadim Demchik .

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  1. National Center for Supercomputing Applications, University of Illinois, Urbana, Illinois, USA

    Volodymyr Kindratenko

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Demchik, V. (2014). Pseudorandom Numbers Generation for Monte Carlo Simulations on GPUs: OpenCL Approach. In: Kindratenko, V. (eds) Numerical Computations with GPUs. Springer, Cham. https://doi.org/10.1007/978-3-319-06548-9_12

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  • DOI: https://doi.org/10.1007/978-3-319-06548-9_12

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  • Online ISBN: 978-3-319-06548-9

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