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Accelerating Genetic Programming through Graphics Processing Units

Wolfgang Banzhaf, Simon Harding, William B. Langdon and Garnett Wilson
Deptartment of Computer Science, Memorial University of Newfoundland, St. John’s, NL, Canada
Genetic Programming Theory and Practice VI, Genetic and Evolutionary Computation, 2009, 1-19

@article{banzhaf2009accelerating,

   title={Accelerating Genetic Programming through Graphics Processing Units.},

   author={Banzhaf, W. and Harding, S. and Langdon, W.B. and Wilson, G.},

   journal={Genetic Programming Theory and Practice VI},

   pages={1–19},

   year={2009},

   publisher={Springer}

}

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Graphics Processing Units (GPUs) are in the process of becoming 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. The true degree of parallelism of GPUs is often hidden from the user, making programming even more flexible and convenient. In this chapter we survey Genetic Programming methods currently ported to GPUs.
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