FPGA implementation of an adaptive genetic algorithm

Mengxu Fang, Tang Bin
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引用次数: 5

Abstract

In this paper, the adaptive genetic algorithm (AGA) is designed use Field Programmable Gate Array (FPGA) based on modular design. First, the FPGA's internal structure and the basic design process are introduced, to Altera Cyclone III series chips as an example. Secondly algorithm of hardware and software environment is introduced. The software is Altera's integrated development software, the Quartus II, development board is SOC/family experiment KX_7C series of experimental development system. Then the AGA is divided into some modules, such as fitness calculation module, control module, population initialization module, selection module, crossover and mutation module, data channel selection module, random number generator module, and memory module, etc. Finally the top-level module is downloaded to the Altera Cyclone III-EP3C40Q240C8N chip, and program is run out and debugged on the development board. Finally we compared the results of the hardware and software running.
FPGA实现的一种自适应遗传算法
本文采用基于模块化设计的现场可编程门阵列(FPGA)设计自适应遗传算法(AGA)。首先介绍了FPGA的内部结构和基本设计过程,以Altera Cyclone III系列芯片为例。其次介绍了算法的硬件和软件环境。该软件是Altera的集成开发软件,Quartus II开发板是SOC/家族实验KX_7C系列实验开发系统。然后将遗传算法划分为适应度计算模块、控制模块、种群初始化模块、选择模块、交叉变异模块、数据通道选择模块、随机数产生模块、存储模块等模块。最后将顶层模块下载到Altera Cyclone III-EP3C40Q240C8N芯片上,在开发板上运行并调试程序。最后对硬件和软件的运行结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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