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A Fair Comparison of Modern CPUs and GPUs Running the Genetic Algorithm under the Knapsack Benchmark

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Applications of Evolutionary Computation (EvoApplications 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7248))

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Abstract

The paper introduces an optimized multicore CPU implementation of the genetic algorithm and compares its performance with a fine-tuned GPU version. The main goal is to show the true performance relation between modern CPUs and GPUs and eradicate some of myths surrounding GPU performance. It is essential for the evolutionary community to provide the same conditions and designer effort to both implementations when benchmarking CPUs and GPUs. Here we show the performance comparison supported by architecture characteristics narrowing the performance gain of GPUs.

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Author information

Authors and Affiliations

  1. ANU College of Engineering and Computer Science, The Australian National University, Canberra, ACT, 0200, Australia

    Jiri Jaros

  2. Faculty of Information Technology, Brno University of Technology, Bozetechova 2, 612 66, Brno, Czech Republic

    Petr Pospichal

Authors
  1. Jiri Jaros
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  2. Petr Pospichal
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Statistics, University of Strathclyde, 16 Richmond Street, G1 1XQ, Glasgow, UK

    Cecilia Di Chio

  2. Financial Mathematics and Computation Cluster Natural Computing Research and Applications Group Complex and Adaptive Systems Laboratory, University College, Dublin, Ireland

    Alexandros Agapitos

  3. Department of Computer Engineering, University of Parma, Viale Usberti 181/a, 43100, Parma, Italy

    Stefano Cagnoni

  4. ETSI Informática, Universidad de Málaga, Campus de Teatinos, 29071, Málaga, Spain

    Carlos Cotta

  5. Centro Universitario de Merida, Universidad de Extremadura, Spain

    Francisco Fernández de Vega

  6. Dalle Molle Institute for Artificial Intelligence (IDSIA), Lugano, Switzerland

    Gianni A. Di Caro

  7. DFKI Bremen, Cyber-Physical Systems, Bremen, Germany

    Rolf Drechsler

  8. Knowledge Engineering Research Group, Aston University, B4 7ET, Aston Triangle, Birmingham, UK

    Anikó Ekárt

  9. Instituto Tecnológico de Informática, Edif. 8G Acceso B, Universidad Politécnica de Valencia, 46022, Valencia, Spain

    Anna I. Esparcia-Alcázar

  10. Next Generation Intelligent Networks Research Center (nexGIN RC), National University of Computer & Emerging Sciences (FAST-NU), Islamabad, Pakistan

    Muddassar Farooq

  11. Department of Computer Science,, University College London, Gower Street, WC1E 6BT, London, UK

    William B. Langdon

  12. Depto. Arquitectura y Tecnologa de Computadores, ETS Ingeiera Informtica, C/Daniel Saucedo Aranda, s/n, 18071, Granada, Spain

    Juan J. Merelo-Guervós

  13. Chair of Algorithm Engineering, Computational Intelligence Group, Dept. of Computer Science, Technische Universität Dortmund, Germany

    Mike Preuss

  14. HTWK Leipzig, Fakultät Elektrotechnik und Informationstechnik, Institut Mess–, Steuerungs– und Regelungstechnik, Postfach 30 11 66, D–04251, Leipzig, Germany

    Hendrik Richter

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

    Sara Silva

  16. Centre for Informatics and Systems, University of Coimbra, Portugal

    Anabela Simões

  17. Dipartimento di Automatica e Informatica, Politecnico di Torino, Italy

    Giovanni Squillero

  18. Institute of High Performance Computing and Networking, ICAR-CNR, Naples, Italy

    Ernesto Tarantino

  19. Dipartimento di Tecnologie dell’Informazione, Universita’ degli Studi di Milano, Italy

    Andrea G. B. Tettamanzi

  20. IT University of Copenhagen, Rued Langaards Vej 7, 2300, Copenhagen, Denmark

    Julian Togelius

  21. Centre for Emergent Computing, Edinburgh Napier University, Edinburgh,, UK

    Neil Urquhart

  22. Department of Computer Engineering, Istanbul Technical University, 34490, Maslak, Turkey

    A. Åžima Uyar

  23. Center For Computer Games Research, IT University Of Copenhagen, Rued Langgaards Vej 7, 2300, Copenhagen, Denmark

    Georgios N. Yannakakis

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© 2012 Springer-Verlag Berlin Heidelberg

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Jaros, J., Pospichal, P. (2012). A Fair Comparison of Modern CPUs and GPUs Running the Genetic Algorithm under the Knapsack Benchmark. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2012. Lecture Notes in Computer Science, vol 7248. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29178-4_43

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  • DOI: https://doi.org/10.1007/978-3-642-29178-4_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29177-7

  • Online ISBN: 978-3-642-29178-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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