Abstract:Stochastic simulations are often sensitive to the source of randomness that characterizes the statistical quality of their results. Consequently, we need highly reliable Random Number Generators (RNGs) to feed such applications. Recent developments try to shrink the computation time by relying more and more General Purpose Graphics Processing Units (GPGPUs) to speed-up stochastic simulations. Such devices bring new parallelization possibilities, but they also introduce new programming difficulties. Since RNGs … Show more
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