Parallelizing HMMER for Hardware Acceleration on FPGAs

Profile based Hidden Markov Model is a widely used tool in bioinformatics. While being very valuable to biologists, it is extremely compute intensive and suffers from prohibitive execution time. We propose an original parallelization scheme of the hmmsearch tool for FPGA technology. We show how to derive a flexible and generic hardware architecture which accelerates the hmmsearch main kernel by two orders of magnitude without modifying its original algorithm.