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A Self-Reconfiguring architecture supporting multiple objective functions in genetic algorithms

Papaefstathiou Ioannis, Effraimidis C., Papadimitriou Kyprianos, Dollas Apostolos

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URI: http://purl.tuc.gr/dl/dias/A7952FD6-E348-4CD9-B005-0ED3BA1584E0
Year 2009
Type of Item Conference Full Paper
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Bibliographic Citation K. Papadimitriou, A. Dollas, I. Papaefstathiou, C. Effraimidis, "A self-reconfiguring architecture supporting multiple objective functions in genetic algorithms," in International Conference on Field Programmable Logic and Applications, 2009, pp. 453 - 456. doi: 10.1109/FPL.2009.5272482 https://doi.org/10.1109/FPL.2009.5272482
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Summary

Genetic algorithms (GA) are search algorithms based on the mechanism of natural selection and genetics. FPGAs have been widely used to implement hardware-based genetic algorithms (HGA) and have provided speedups of up to three orders of magnitude as compared to their software counterparts. In this paper, we propose a parameterized partially reconfigurable HGA architecture (PPR-HGA). The novelty of this architecture is that it allows for the objective function to be updated through partial reconfiguration, and supports various genetic parameters.

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