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Random generators for parallel processing

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Given the growing interest in parallel processing through GPUs or multiple processors, there is a clear need for a proper use of (uniform) random number generators in this environment. We were discussing the issue yesterday with Jean-Michel Marin and briefly looked at a few solutions:

Obviously, we did not do any serious search in the recent literature and there are many other approaches to be found in the computer literature, including the scalable parallel random number generation (SPRNG) packages of Michael Mascagni (including an R version) and Matsumoto’s dynamic creator, a C program that provides starting values for independent streams when using the Mersenne twister.


Filed under: R, Statistics Tagged: Mersenne twister, Monte Carlo methods, parallel processing, random number generation, SPRNG

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