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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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Conference Publications in Community School of Electrical and Computer Engineering

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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