The Viterbi algorithm is one of the most used dynamic programming algorithms for protein comparison and identification, based on hidden markov Models (HMMs). Most of the works in the literature focus on the implementation of hardware accelerators that act as a prefilter stage in the comparison process. This stage discards poorly aligned sequences with a low similarity score and forwards sequences with good similarity scores to software, where they are reprocessed to generate the sequence alignment. In order to reduce the software reprocessing time, this work proposes a hardware accelerator for the Viterbi algorithm which includes the concept of divergence, in which the region of interest of the dynamic programming matrices is delimited. We obtained gains of up to 182x when compared to unaccelerated software. The performance measurement methodology adopted in this work takes into account not only the acceleration achieved by the hardware but also the reprocessing software stage required to generate the alignment.
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