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Fast Genetic Programming on GPUs

  • Simon Harding
  • Wolfgang Banzhaf
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4445)

Abstract

As is typical in evolutionary algorithms, fitness evaluation in GP takes the majority of the computational effort. In this paper we demonstrate the use of the Graphics Processing Unit (GPU) to accelerate the evaluation of individuals. We show that for both binary and floating point based data types, it is possible to get speed increases of several hundred times over a typical CPU implementation. This allows for evaluation of many thousands of fitness cases, and hence should enable more ambitious solutions to be evolved using GP.

Keywords

Genetic programming Graphics Card Acceleration Parallel Evaluation 

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Simon Harding
    • 1
  • Wolfgang Banzhaf
    • 1
  1. 1.Computer Science Department, Memorial University, Newfoundland 

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