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

Summarization: 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.Παρουσιάστηκε στο: International Conference on Field Programmable Logic and Applications, 200