Accelerating evolutionary computation with graphics processing units

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Accelerating evolutionary computation with graphics processing units

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Genetic And Evolutionary Computation Conference archive
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers table of contents

Montreal, Québec, Canada

TUTORIAL SESSION: Tutorials table of contents

Pages 3237-3286

Year of Publication: 2009

ISBN:978-1-60558-505-5

Authors

Wolfgang Banzhaf	Memorial University, St John's, NF, Canada
Simon Harding	Memorial University, St John's, NF, Canada

Sponsors

SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
ACM: Association for Computing Machinery

Publisher

ACM New York, NY, USA

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ABSTRACT

Graphics Processing Units (GPUs) have become a major source of computational power for numerical applications. Originally designed for application of time-consuming graphics operations, GPUs are stream processors that implement the SIMD paradigm. Modern programming tools allow developers to access the parallelism of the GPU in a flexible and convenient way, hiding many low level details from the user.

In this tutorial we shall provide a gentle introduction of how to put GPUs to good use with Evolutionary Computation.

INDEX TERMS

Primary Classification:
D. Software
D.1 PROGRAMMING TECHNIQUES
D.1.3 Concurrent Programming