most citedReproducibility, energy efficiency and performance of pseudorandom number generators in machine learning: a comparative study of python, numpy, tensorflow, and pytorch implementations

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cs.DC2026

ASSESSING THE STOCHASTIC PROPERTIES OF MODERN PSEUDO-RANDOM GENERATORS FOR PARALLEL COMPUTING

Théau Wartel, David R. C. Hill

Pseudo-random number generators (PRNGs) are widely used in modern computing and are expected to exhibit excellent statistical performance and repeatability. This study evaluates an…

cs.DC2024

Identifying Quality Mersenne Twister Streams For Parallel Stochastic Simulations

Benjamin Antunes, Claude Mazel, David R. C Hill

The Mersenne Twister (MT) is a pseudo-random number generator (PRNG) widely used in High Performance Computing for parallel stochastic simulations. We aim to assess the quality of…