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PRAND: GPU accelerated parallel random number generation library: Using most reliable algorithms and applying parallelism of modern GPUs and CPUs

L.Yu. Barash, L.N. Shchur
Landau Institute for Theoretical Physics, 142432 Chernogolovka, Russia
arXiv:1307.5869 [physics.comp-ph], (22 Jul 2013)
@article{2013arXiv1307.5869B,

   author={Barash}, L.~Y. and {Shchur}, L.~N.},

   title={"{PRAND: GPU accelerated parallel random number generation library: Using most reliable algorithms and applying parallelism of modern GPUs and CPUs}"},

   journal={ArXiv e-prints},

   archivePrefix={"arXiv"},

   eprint={1307.5869},

   primaryClass={"physics.comp-ph"},

   keywords={Physics – Computational Physics, Computer Science – Mathematical Software},

   year={2013},

   month={jul},

   adsurl={http://adsabs.harvard.edu/abs/2013arXiv1307.5869B},

   adsnote={Provided by the SAO/NASA Astrophysics Data System}

}

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The library PRAND for pseudorandom number generation for modern CPUs and GPUs is presented. It contains both single-threaded and multi-threaded realizations of a number of modern and most reliable generators recently proposed and studied in [1,2,3,4,5] and the efficient SIMD realizations proposed in [6]. One of the useful features for using PRAND in parallel simulations is the ability to initialize up to $10^{19}$ independent streams. Using massive parallelism of modern GPUs and SIMD parallelism of modern CPUs substantially improves performance of the generators.
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