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Parallel Random Number Generators Based on Large Order Multiple Recursive Generators

In: Monte Carlo and Quasi-Monte Carlo Methods 2008

Author

Listed:
  • Lih-Yuan Deng

    (University of Memphis, Department of Mathematical Sciences)

  • Jyh-Jen Horng Shiau

  • Gwei-Hung Tsai

Abstract

Classical random number generators like Linear Congruential Generators (LCG) and Multiple Recursive Generators (MRG) are popular for large-scale simulation studies. To speed up the simulation process, a systematic method is needed to construct and parallelize the random number generators so that they can run simultaneously on several computers or processors. LCGs and MRGs have served as baseline generators for some parallel random number generator (PRNG) constructed in the literature. In this paper, we consider the parallelization problem particularly for a general class of efficient and portable large-order MRGs, in which most coefficients of the recurrence equation are nonzero. With many nonzero terms, such MRGs have an advantage over the MRGs with just a few nonzero terms that they can recover more quickly from a bad initialization. With the special structure imposed on the nonzero coefficients of the new class of generators, the proposed PRNGs can be implemented efficiently. A method of automatic generation of the corresponding MRGs for parallel computation is presented.

Suggested Citation

  • Lih-Yuan Deng & Jyh-Jen Horng Shiau & Gwei-Hung Tsai, 2009. "Parallel Random Number Generators Based on Large Order Multiple Recursive Generators," Springer Books, in: Pierre L' Ecuyer & Art B. Owen (ed.), Monte Carlo and Quasi-Monte Carlo Methods 2008, pages 289-296, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-04107-5_17
    DOI: 10.1007/978-3-642-04107-5_17
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