Abstract
AbstractPseudo-random number generation is a fundamental problem in computer programming. In the case of sequential processing the problem is very well researched, but parallel processing raises new problems whereof far too little is currently understood. Splittable pseudo-random generators (S-PRNG) have been proposed to meet the challenges of parallelism. While applicable to any programming paradigm, they are designed to be particularly suitable for pure functional programming. In this paper, we review and evaluate known constructions of such generators, and we identify flaws in several large classes of generators, including Lehmer trees, the implementation in Haskell's standard library, leapfrog, and subsequencing (substreaming).
Publisher
Cambridge University Press (CUP)
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Type-Level Property Based Testing;Proceedings of the 9th ACM SIGPLAN International Workshop on Type-Driven Development;2024-08-28
2. LXM: better splittable pseudorandom number generators (and almost as fast);Proceedings of the ACM on Programming Languages;2021-10-20
3. GeantV;Computing and Software for Big Science;2021-01-03
4. Vectorization of random number generation and reproducibility of concurrent particle transport simulation;Journal of Physics: Conference Series;2020-04-01
5. Reproducible parallel simulation experiments via pure functional programming;2019 IEEE/ACM 23rd International Symposium on Distributed Simulation and Real Time Applications (DS-RT);2019-10