Evolutionary Computing on Consumer-Level Graphics Hardware
The Chinese University of Hong Kong
IEEE Intelligent Systems, Volume 22, Issue 2, p.69-78
@article{fok2007evolutionary,
title={Evolutionary computing on consumer graphics hardware},
author={Fok, K.L. and Wong, T.T. and Wong, M.L.},
journal={Intelligent Systems, IEEE},
volume={22},
number={2},
pages={69–78},
issn={1541-1672},
year={2007},
publisher={IEEE}
}
We propose implementing a parallel EA on consumer graphics cards, which we can find in many PCs. This lets more people use our parallel algorithm to solve large-scale, real-world problems such as data mining. Parallel evolutionary algorithms run on consumer-grade graphics hardware achieve better execution times than ordinary evolutionary algorithms and offer greater accessibility than those run on high-performance computers
January 23, 2011 by hgpu
