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Probability, Parallelism and the State Space Exploration Problem

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Computer Performance Evaluation (TOOLS 1998)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1469))

Abstract

We present a new dynamic probabilistic state exploration algorithm based on hash compaction. Our method has a low state omission probability and low memory usage that is independent of the length of the state vector. In addition, the algorithm can be easily parallelised. This combination of probability and parallelism enables us to rapidly explore state spaces that are an order of magnitude larger than those obtainable using conventional exhaustive techniques. We implement our technique on a distributed-memory parallel computer and we present results showing good speedups and scalability. Finally, we discuss suitable choices for the three hash functions upon which our algorithm is based.

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Author information

Authors and Affiliations

  1. Department of Computing, Imperial College, 180 Queens Gate, London, SW7 2BZ, UK

    William Knottenbelt & Peter Harrison

  2. Computer Science Department, University of Cape Town, Rondebosch, 7701, South Africa

    Mark Mestern & Pieter Kritzinger

Authors
  1. William Knottenbelt
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  2. Mark Mestern
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  3. Peter Harrison
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  4. Pieter Kritzinger
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Editor information

Editors and Affiliations

  1. Departament de Ciencies Matematiques i Informàtica, Universitat de les Illes Balears, Careterra de Valldemossa km 7.6, E-07071, Palma (Balears), Spain

    Ramon Puigjaner , Nunzio N. Savino  & Bartomeu Serra ,  & 

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© 1998 Springer-Verlag Berlin Heidelberg

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Knottenbelt, W., Mestern, M., Harrison, P., Kritzinger, P. (1998). Probability, Parallelism and the State Space Exploration Problem. In: Puigjaner, R., Savino, N.N., Serra, B. (eds) Computer Performance Evaluation. TOOLS 1998. Lecture Notes in Computer Science, vol 1469. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-68061-6_14

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  • DOI: https://doi.org/10.1007/3-540-68061-6_14

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64949-6

  • Online ISBN: 978-3-540-68061-1

  • eBook Packages: Springer Book Archive

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