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Some Methods of Parallel Pseudorandom Number Generation

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Algorithms for Parallel Processing

Part of the book series: The IMA Volumes in Mathematics and its Applications ((IMA,volume 105))

Abstract

We detail several methods used in the production of pseudorandom numbers for scalable systems. We will focus on methods based on parameterization, meaning that we will not consider splitting methods. We describe parameterized versions of the following pseudorandom number generators:

  1. 1.

    linear congruential generators

  2. 2.

    linear matrix generators

  3. 3.

    shift-register generators

  4. 4.

    lagged-Fibonacci generators

  5. 5.

    inversive congruential generators

We briefly describe the methods, detail some advantages and disadvantages of each method and recount results from number theory that impact our understanding of their quality in parallel applications. Several of these methods are currently part of scalable library for pseudorandom number generation, called SPRNG and available at the URL: www.ncsa.uiuc.edu/Apps/SPRNG.

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Author information

Authors and Affiliations

  1. Program in Scientific Computing and Department of Mathematics, University of Southern Mississippi, Southern Station, Box 10057, Hattiesburg, MS, 39406-0057, USA

    Michael Mascagni

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  1. Michael Mascagni
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Illinois at Urbana, Urbana, IL, 61801-2987, USA

    Michael T. Heath

  2. Department of Computer Science and Engineering, Indian Institute of Technology, Powai, Mumbai, 400076, India

    Abhiram Ranade

  3. Hewlett-Packard, Inc., Palo Alto, CA, 94305-1126, USA

    Robert S. Schreiber

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Mascagni, M. (1999). Some Methods of Parallel Pseudorandom Number Generation. In: Heath, M.T., Ranade, A., Schreiber, R.S. (eds) Algorithms for Parallel Processing. The IMA Volumes in Mathematics and its Applications, vol 105. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1516-5_12

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  • DOI: https://doi.org/10.1007/978-1-4612-1516-5_12

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-7175-8

  • Online ISBN: 978-1-4612-1516-5

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