gpu加速标准和多种群文化算法

Jianqiang Dong, Bo Yuan
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引用次数: 1

摘要

在本文中,我们提出了三种使用cuda支持的gpu的并行文化算法。首先,我们使用GPU来加速一个昂贵的适应度函数。其次,给出了标准ca和多种群ca的并行版本。实验表明,具有昂贵适应度函数的标准CA的速度提高了600倍以上。在轻量级基准测试问题上,标准CA的加速仅为3-4倍,而多种群CA仍然可以实现30-50倍的加速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GPU-Accelerated Standard and Multi-population Cultural Algorithms
In this paper, we present three parallel cultural algorithms using CUDA-enabled GPUs. Firstly, we used the GPU to accelerate an expensive fitness function. Next, the parallel versions of both standard and multi-population CAs were presented. Experiments show that the standard CA with an expensive fitness function was made more than 600 times faster. On lightweight benchmark problems, the speedups were only 3-4 times for the standard CA while the multi-population CA can still achieve 30-50 times speedups.
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