This paper describes how the massive parallelism of the rapidly reconfigurable Xilinx XC6216 FPGA (in conjunction with Virtual Computing's H.O.T. Works board) can be exploited to accelerate the time-consuming fitness measurement task of genetic algorithms and genetic programming. This acceleration is accomplished by embodying each individual of the evolving population into hardware in order to perform the fitness measurement task. A 16-step sorting network for seven items was evolved that has two fewer steps than the sorting network described in the 1962 O'Connor and Nelson patent on sorting networks (and the same number of steps as a 7-sorter that was devised by Floyd and Knuth subsequent to the patent and that is now known to be minimal). Other minimal sorters have been evolved.
本文描述了如何利用快速可重新配置的Xilinx XC6216 FPGA(与虚拟计算的H.O.T.工程板)的大规模平行性如何利用以加速遗传算法和遗传编程的耗时的健身测量任务。通过将不断发展的人口的人体现成硬件来实现这种加速度来实现,以便执行健身测量任务。演化了七个项目的16步分类网络,这些网络具有比1962年O'Connor和纳尔逊专利中描述的排序网络(以及与弗洛伊德设计的7分拣机相同数量的步骤在专利之后的Knuth,现在已知是最小的)。其他最小分拣机已经进化。 p>
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