遗传算法模型的硬件利用

V. Skorpil, V. Oujezský, Martin Tuleja
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引用次数: 2

摘要

对遗传算法(GA)的模型进行了比较。重点研究了并行遗传算法,即主从遗传算法、粗粒度遗传算法和细粒度遗传算法模型。所得结果与序列模型进行了比较。进行了主内存使用比较和中央处理器单元(CPU)比较。并在多个工作站上对并行化模块进行了验证,并对测试结果进行了评估。正如预期的那样,串行模型具有最低的主内存需求。对于增加人口规模的并行化模型,主内存使用量也会增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hardware Utilization of Models of Genetic Algorithms
The paper compares the models of Genetic Algorithms (GA). It is focused on parallelized genetic algorithms, namely on the models of Master-Slave GA, Coarse-Grained GA, and Fine-Grained GA. The obtained results were compared with a serial model. A main memory usage comparison and a Central Processor Unit (CPU) comparison were performed. Furthermore, the parallelization module was verified on several workstations and the testing was evaluated. As expected, the serial model had the lowest main memory requirements. For parallelized models with increasing population size, main memory usage also increased.
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