4.6 Article

EASEA: specification and execution of evolutionary algorithms on GPGPU

期刊

SOFT COMPUTING
卷 16, 期 2, 页码 261-279

出版社

SPRINGER
DOI: 10.1007/s00500-011-0718-z

关键词

Evolutionary computation; Evolution strategy; Genetic algorithm; Genetic programming; Memetic algorithm; CUDA; GPGPUs

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EASEA is a framework designed to help non-expert programmers to optimize their problems by evolutionary computation. It allows to generate code targeted for standard CPU architectures, GPGPU-equipped machines as well as distributed memory clusters. In this paper, EASEA is presented by its underlying algorithms and by some example problems. Achievable speedups are also shown onto different NVIDIA GPGPUs cards for different optimization algorithm families.

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