Accelerating the viterbi algorithm for profile hidden markov models using reconfigurable hardware

Authors:
Timothy F. Oliver;Bertil Schmidt;Yanto Jakop;Douglas L. Maskell
Affiliations:
School of Computer Engineering, Nanyang Technological University, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore
Venue:
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part I
Year:
2006

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Abstract

Profile Hidden Markov Models (PHMMs) are used as a popular tool in bioinformatics for probabilistic sequence database searching. The search operation consists of computing the Viterbi score for each sequence in the database with respect to a given query PHMM. Because of the rapid growth of biological sequence databases, finding fast solutions is of highest importance to research in this area. Unfortunately, the required scan times of currently available sequential software implementations are very high. In this paper we show how reconfigurable hardware can be used as a computational platform to accelerate this application by two orders of magnitude.