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An Implementation of Evolutionary Computation Operators in OpenCL

  • István Lőrentz
  • Răzvan Andonie
  • Mihaela Maliţa
Part of the Studies in Computational Intelligence book series (SCI, volume 382)

Abstract

We discuss the parallel implementation of Genetic Algorithms and Evolution Strategy on General-Purpose Graphical Units, using the OpenCL framework. Multiple evolutionary operators are tested (tournament, roulette wheel selection, uniform and Gaussian mutation, crossover, recombination), as well as different approaches for parallelism, for small and large problem sizes. We use the Island Model of Parallel GA, with random migration. Performance is measured using two graphic cards: NVidia GeForce GTX 560Ti and AMD Radeon 6950. Tests are performed in a distributed grid, using the Java Parallel Processing Framework.

Keywords

Local Memory Global Memory Graphic Card Single Instruction Multiple Data Compute Unit 
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 2011

Authors and Affiliations

  • István Lőrentz
    • 1
  • Răzvan Andonie
    • 2
    • 1
  • Mihaela Maliţa
    • 3
  1. 1.Electronics and Computers DepartmentTransylvania UniversityBraşovRomania
  2. 2.Computer Science DepartmentCentral Washington University EllensburgUSA
  3. 3.Computer Science DepartmentSaint Anselm College ManchesterUSA

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