A Self-Reconfiguring Architecture Supporting Multiple Objective Functions in Genetic Algorithms

Provided by: Technical University of Cluj-Napoca
Topic: Hardware
Format: PDF
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, the authors propose 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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