Flexible implementation of genetic algorithms on FPGAs

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Flexible implementation of genetic algorithms on FPGAs
In this paper, we propose a technique to flexibly implement genetic algorithms for various problems on FPGAs. For the purpose, we propose a basic architecture for GA which consists of several modules for GA operations to compose a GA pipeline, and a parallel architecture consisting of multiple concurrent pipelines. The proposed architectures are simple enough to be implemented on FPGAs, applicable to various problems such as Knapsack Problem and Traveling Salesman Problem (TSP), and easy to estimate the size of the resulting circuit. We also propose a model for predicting the size of resulting circuit from given parameters consisting of the problem size, the number of concurrent pipelines, and the number of candidate solutions for GA. Based on the proposed method, we have implemented a tool to facilitate GA circuit design and development. This tool allows designers to find appropriate parameter values so that the resulting circuit can be accommodated in the target FPGA device, and to ...
Tatsuhiro Tachibana, Yoshihiro Murata, Naoki Shiba
Added 22 Aug 2010
Updated 17 Jun 2012
Type Conference
Year 2006
Where FPGA
Authors Tatsuhiro Tachibana, Yoshihiro Murata, Naoki Shibata, Keiichi Yasumoto, Minoru Ito
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