Title

Parallel evolutionary algorithms on graphics processing unit

Document Type

Conference paper

Source Publication

Proceedings of the 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005

Publication Date

1-1-2005

First Page

2286

Last Page

2293

Publisher

Institute of Electrical and Electronics Engineers

Abstract

Evolutionary Algorithms (EAs) are effective and robust methods for solving many practical problems such as feature selection, electrical circuits synthesis, and data mining. However, they may execute for a long time for some difficult problems, because several fitness evaluations must be performed. A promising approach to overcome this limitation is to parallelize these algorithms. In this paper, we propose to implement a parallel EA on consumer-level graphics cards. We perform experiments to compare our parallel EA with an ordinary EA and demonstrate that the former is much more effective than the latter. Since consumer-level graphics cards are available in ubiquitous personal computers and these computers are easy to use and manage, more people will be able to use our parallel algorithm to solve their problems encountered in real-world applications.

DOI

10.1109/CEC.2005.1554979

Publisher Statement

Copyright © 2005 IEEE. Access to external full text or publisher's version may require subscription.

Additional Information

Paper presented at the 2005 IEEE Congress on Evolutionary Computation (IEEE CEC 2005), 2-5 September 2005, Edinburgh, Scotland.

ISBN of the source publication: 0780393635

Full-text Version

Publisher’s Version

Recommended Citation

Wong, M.-L., Wong, T.-T., & Fok, K.-L. (2005). Parallel evolutionary algorithms on graphics processing unit. In Proceedings of the 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005 (pp. 2286-2293). Piscataway: Institute of Electrical and Electronics Engineers. doi: 10.1109/CEC.2005.1554979

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