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Handbook of Optimization pp 845–867Cite as

GPU Based Enhanced Differential Evolution Algorithm: A Comparison between CUDA and OpenCL

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Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 38))

Abstract

A GPU based enhanced differential evolution algorithm is presented in this chapter to solve the flow shop scheduling problem. The main premise is to show the effectiveness of using mainstream GPU hardware compared to high-end CPU, and analyze as to under what conditions it becomes viable. Both CUDA and OpenCL architecture is utilized and a comparison is done on the Mac OS X platform. The results validate that with increasing problem complexity, GPU programming becomes more viable.

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References

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Author information

Authors and Affiliations

  1. Department of Computing Science, Faculty of Electrical Engineering and Computing Science, Technical University of Ostrava, Tr. 17. Listopadu 15, Ostrava, Czech Republic

    Donald David Davendra & Ivan Zelinka

Authors
  1. Donald David Davendra
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  2. Ivan Zelinka
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Corresponding author

Correspondence to Donald David Davendra .

Editor information

Editors and Affiliations

  1. Technical University of Ostrava, 17. listopadu 15, Ostrava-Porub, 708 33, Czech Republic

    Ivan Zelinka

  2. , Faculty of Electrical Engineering and, Technical University of Ostrava, 17. listopadu 15, Ostrava-Poruba, 708 33, Czech Republic

    Václav Snášel

  3. Auburn, 98071, USA

    Ajith Abraham

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Davendra, D.D., Zelinka, I. (2013). GPU Based Enhanced Differential Evolution Algorithm: A Comparison between CUDA and OpenCL. In: Zelinka, I., Snášel, V., Abraham, A. (eds) Handbook of Optimization. Intelligent Systems Reference Library, vol 38. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30504-7_33

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  • DOI: https://doi.org/10.1007/978-3-642-30504-7_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30503-0

  • Online ISBN: 978-3-642-30504-7

  • eBook Packages: EngineeringEngineering (R0)

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