Reliable Initialization of GPU-enabled Parallel Stochastic Simulations Using Mersenne Twister for Graphics Processors
ISIMA, Institut Superieur d’Informatique, de Modelisation et de ses Appplications, BP 10125, F-63173, AUBIERE
arXiv:1501.07701 [cs.DC], (30 Jan 2015)
@article{passerat-palmbach2015reliable,
title={Reliable Initialization of GPU-enabled Parallel Stochastic Simulations Using Mersenne Twister for Graphics Processors},
author={Passerat-Palmbach, Jonathan},
year={2015},
month={jan},
archivePrefix={"arXiv"},
primaryClass={cs.DC}
}
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). Consequently, 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.
February 2, 2015 by hgpu
