Reliable Initialization of GPU-enabled Parallel Stochastic Simulations Using Mersenne Twister for Graphics Processors

Abstract : Parallel stochastic simulations tend to exploit more and more computing power and they are now also developed for General Purpose Graphics Process Units (GP-GPUs). Conse-quently, they need reliable random sources to feed their applications. We propose a survey of the current Pseudo Random Numbers Generators (PRNG) available on GPU. We give a particular focus to the recent Mersenne Twister for Graphics Processors (MTGP) that has just been released. Our work provides empirically checked statuses designed to initialize a particular configuration of this generator, in order to prevent any potential bias introduced by the parallelization of the PRNG.
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https://hal.inria.fr/hal-01083150
Contributor : Jonathan Passerat-Palmbach <>
Submitted on : Thursday, January 29, 2015 - 11:58:48 PM
Last modification on : Thursday, April 4, 2019 - 10:18:07 AM

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Distributed under a Creative Commons Attribution 4.0 International License

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  • HAL Id : hal-01083150, version 2
  • ARXIV : 1501.07701

Citation

Jonathan Passerat-Palmbach, Claude Mazel, Antoine Mahul, David R.C. Hill. Reliable Initialization of GPU-enabled Parallel Stochastic Simulations Using Mersenne Twister for Graphics Processors. European Simulation and Modelling 2010, Oct 2010, Essen, Belgium. pp.187 - 195. ⟨hal-01083150v2⟩

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