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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.