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A Many Threaded CUDA Interpreter for Genetic Programming

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Book cover Genetic Programming (EuroGP 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6021))

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Abstract

A Single Instruction Multiple Thread CUDA interpreter provides SIMD like parallel evaluation of the whole GP population of \(\frac{1}{4}\) million reverse polish notation (RPN) expressions on graphics cards and nVidia Tesla. Using sub-machine code tree GP a sustain peak performance of 665 billion GP operations per second (10,000 speed up) and an average of 22 peta GP ops per day is reported for a single GPU card on a Boolean induction benchmark never attempted before, let alone solved.

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Author information

Authors and Affiliations

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

    W. B. Langdon

Authors
  1. W. B. Langdon
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Editor information

Editors and Affiliations

  1. Instituto Tecnologico de Informatica, Universidad Politecnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain

    Anna Isabel Esparcia-Alcázar

  2. Computer Science, Aston Triangle, Aston University, B4 7ET, Birmingham, UK

    Anikó Ekárt

  3. INESC-ID Lisboa, Rua Alves Redol 9, 1000-029, Lisboa, Portugal

    Sara Silva

  4. School of Computer Science and Electronic Engineering, University of Essex, Wivenhoe Park, CO4 3SQ, Colchester, UK

    Stephen Dignum

  5. Computer Engineering Department, Istanbul Technical University, Room Nr. 3302, 34469, Maslak, Istanbul, Turkey

    A. Şima Uyar

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© 2010 Springer-Verlag Berlin Heidelberg

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Langdon, W.B. (2010). A Many Threaded CUDA Interpreter for Genetic Programming. In: Esparcia-Alcázar, A.I., Ekárt, A., Silva, S., Dignum, S., Uyar, A.Ş. (eds) Genetic Programming. EuroGP 2010. Lecture Notes in Computer Science, vol 6021. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12148-7_13

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  • DOI: https://doi.org/10.1007/978-3-642-12148-7_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12147-0

  • Online ISBN: 978-3-642-12148-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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