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Parallel Genetic Algorithm on the CUDA Architecture

  • Petr Pospichal
  • Jiri Jaros
  • Josef Schwarz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6024)

Abstract

This paper deals with the mapping of the parallel island-based genetic algorithm with unidirectional ring migrations to nVidia CUDA software model. The proposed mapping is tested using Rosenbrock’s, Griewank’s and Michalewicz’s benchmark functions. The obtained results indicate that our approach leads to speedups up to seven thousand times higher compared to one CPU thread while maintaining a reasonable results quality. This clearly shows that GPUs have a potential for acceleration of GAs and allow to solve much complex tasks.

Keywords

Graphic Processing Unit Benchmark Function Graphic Card Graphic Hardware Single Instruction Multiple Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Petr Pospichal
    • 1
  • Jiri Jaros
    • 1
  • Josef Schwarz
    • 1
  1. 1.Faculty of Information Technology, Department of Computer SystemsBrno University of TechnologyBrnoCzech Republic

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