Generating high-quality random numbers in parallel by cellular automata

Marco Tomassini, Moshe Sipper, Mosé Zolla, Mathieu Perrenoud

Research output: Contribution to journalArticlepeer-review

58 Scopus citations


Many important computer simulation methods rely on random numbers, including Monte Carlo techniques, Brownian dynamics, and stochastic optimization methods such as simulated annealing. Several deterministic algorithms for producing random numbers have been proposed to date. In this paper we concentrate on generating pseudo-random sequences by using cellular automata, which offer a number of advantages over other methods, especially where hardware implementation is concerned. We study both hand-designed random number generators as well as ones produced by artificial evolution. Applying an extensive suite of tests we demonstrate that cellular automata can be used to rapidly produce high-quality random number sequences. Such automata can be efficiently implemented in hardware, can be used in such applications as VLSI built-in self-test, and can be applied in the field of parallel computation.

Original languageEnglish
Pages (from-to)291-305
Number of pages15
JournalFuture Generation Computer Systems
Issue number2
StatePublished - 1 Jan 1999
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications


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