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
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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