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Random Sampling Techniques in Parallel Algorithms

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Advances in Randomized Parallel Computing

Part of the book series: Combinatorial Optimization ((COOP,volume 5))

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Abstract

Random sampling is an important tool in the design of parallel algorithms. Using random sampling it is possible to obtain simple parallel algorithms which are efficient in practice. We will focus on the use of random sampling in fundamental problems such as sorting, selection, list ranking and graph connectivity.

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Author information

Authors and Affiliations

  1. Department of Computer Science, King’s College London, Strand, London, WC2R 2LS, UK

    Rajeev Raman

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  1. Rajeev Raman
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Editor information

Editors and Affiliations

  1. University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos  & Sanguthevar Rajasekaran  & 

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© 1999 Kluwer Academic Publishers

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Raman, R. (1999). Random Sampling Techniques in Parallel Algorithms. In: Pardalos, P.M., Rajasekaran, S. (eds) Advances in Randomized Parallel Computing. Combinatorial Optimization, vol 5. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-3282-4_3

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  • DOI: https://doi.org/10.1007/978-1-4613-3282-4_3

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-3284-8

  • Online ISBN: 978-1-4613-3282-4

  • eBook Packages: Springer Book Archive

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