Random number generators for the large-scale Monte-Carlo simulations

Monte Carlo simulations needs random numbers. History shows how problems with the quality of the PRN does biased results of Monte Carlo simulations. It happens with the higher scale of the simulations. Many improvements was made to make PRN generators more reliable and safe. Attention should be paid also for the possible influence of the correlations due to the high parallelism in the simulations. In the presentation we will present discussion of the problems and solutions for the massive parallel simulations on the clusters. We will present details of our approach and the corresponding libraries [1,2]. Examples will include generation of uncorrelated parallel streams of PRN using CPU, GPU, and CPU extensions SSE2, AVX2, and new AVX512 technology.

[1] Guskova M., Barash L. Y., L.N. Shchur. RNGAVXLIB: Program library for random number generation, AVX realization, Computer Physics Communications. 2016, vol 200, pp. 402-405.
[2] Barash L. Y., Shchur L. PRAND: GPU accelerated parallel random number generation library: Using most reliable algorithms and applying parallelism of modern GPUs and CPUs, Computer Physics Communications. 2014. vol. 185. pp. 1343-1353.