An extended library of hardware modules for genetic algorithms, with applications to DNA sequence matching

Genetic algorithms (GAs) are intelligent search techniques based on the theory of evolution. Software GAs typically require a long processing time. The inherent parallelism in GAs motivates their implementation in hardware. This project extends an existing library of GA hardware modules and performs a comparative analysis of performance for various module choices. A sample architecture developed using the modules is applied to DNA sequence alignment and its performance is compared with the standard software algorithm ClustalW.