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Parallel Programs Are More Evolvable than Sequential Programs

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Genetic Programming (EuroGP 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2610))

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Abstract

This paper presents a novel phenomenon of the Genetic Parallel Programming (GPP) paradigm - the GPP accelerating phenomenon. GPP is a novel Linear Genetic Programming representation for evolving parallel programs running on a Multi-ALU Processor (MAP). We carried out a series of experiments on GPP with different number of ALUs. We observed that parallel programs are more evolvable than sequential programs. For example, in the Fibonacci sequence regression experiment, evolving a 1-ALU sequential program requires 51 times on average of the computational effort of an 8-ALU parallel program. This paper presents three benchmark problems to show that the GPP can accelerate evolution of parallel programs. Due to the accelerating evolution phenomenon of GPP over sequential program evolution, we could increase the normal GP’s evolution efficiency by evolving a parallel program by GPP and if there is a need, the evolved parallel program can be translated into a sequential program so that it can run on conventional hardware.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, China

    Kwong Sak Leung & Kin Hong Lee

  2. Department of Computing, Hong Kong Institute of Vocational Education (Kwai Chung), 20 Hing Shing Road, Kawi Chung, Hong Kong, China

    Sin Man Cheang

Authors
  1. Kwong Sak Leung
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  2. Kin Hong Lee
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  3. Sin Man Cheang
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Editor information

Editors and Affiliations

  1. Computer Science and Information Systems, University of Limerick, Limerick, Ireland

    Conor Ryan

  2. Department of Computer Science, University of Idaho, 83844-1010, Moscow, ID, USA

    Terence Soule

  3. Department of Computer Science, Free University of Amsterdam, 1081, HV Amsterdam, The Netherlands

    Maarten Keijzer

  4. Department of Computer Science, University of Essex, Wivenhoe Park, CO4 3SQ, Colchester, UK

    Edward Tsang  & Riccardo Poli  & 

  5. Department of Computer Science, University of Coimbra, Polo II, Pinhal Marrocos, 3030-290, Coimbra, Portugal

    Ernesto Costa

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© 2003 Springer-Verlag Berlin Heidelberg

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Leung, K.S., Lee, K.H., Cheang, S.M. (2003). Parallel Programs Are More Evolvable than Sequential Programs. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E., Poli, R., Costa, E. (eds) Genetic Programming. EuroGP 2003. Lecture Notes in Computer Science, vol 2610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36599-0_10

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  • DOI: https://doi.org/10.1007/3-540-36599-0_10

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00971-9

  • Online ISBN: 978-3-540-36599-0

  • eBook Packages: Springer Book Archive

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