Self-organizing Migration Algorithm on GPU with CUDA

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 188)

Abstract

A modification of Self-organizing migration algorithm for general-purpose computing on graphics processing units is proposed in this paper. The algorithm is implemented in C++ with its core parts in c-CUDA. Its implementation details and performance are evaluated and compared to previous, pure C++ version of algorithm. 6 commonly used artificial test functions are used to test the performance. The test results clearly show significant speed gains without a compromise in convergence quality.

Keywords

SOMA CUDA GPGPU evolutionary algorithm 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Faculty of Applied InformaticsTomas Bata University in ZlinZlínCzech Republic

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