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Some Simple and Practical Strategies for Parallelism

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Algorithms for Parallel Processing

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

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Abstract

Distributed data structures (DDSs) have the potential to enhance existing paradigms of parallelism and to enable new ones. We review here instances in which this potential has been realized in the form of two DDSs-based techniques for developing parallel applications that are conceptually simple, practical and efficient.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Yale University, New Haven, CT, 06520, USA

    Nicholas Carriero & David Gelernter

  2. Scientific Computing Associates, Inc., 265 Church Street, New Haven, CT, 06510, USA

    Nicholas Carriero & David Gelernter

Authors
  1. Nicholas Carriero
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  2. David Gelernter
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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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© 1999 Springer Science+Business Media New York

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Carriero, N., Gelernter, D. (1999). Some Simple and Practical Strategies for Parallelism. 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_4

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  • DOI: https://doi.org/10.1007/978-1-4612-1516-5_4

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-7175-8

  • Online ISBN: 978-1-4612-1516-5

  • eBook Packages: Springer Book Archive

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