Abstract
GPGPU cards are very difficult to program efficiently. This chapter explains how the EASEA and EASEA-CLOUD platforms can implement different evolution engines efficiently in a massively parallel way that can also serve as a starting point for more complex projects.
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Collet, P., Krüger, F., Maitre, O. (2013). Automatic Parallelization of EC on GPGPUs and Clusters of GPGPU Machines with EASEA and EASEA-CLOUD. In: Tsutsui, S., Collet, P. (eds) Massively Parallel Evolutionary Computation on GPGPUs. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37959-8_3
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DOI: https://doi.org/10.1007/978-3-642-37959-8_3
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