A Three-Level Scoring System for Fast Similarity Evaluation Based on Smith-Waterman Algorithm

The Smith-Waterman (S-W) algorithm is widely adopted by the state-of-the-art DNA sequence aligners in next-generation sequencing (NGS). Prevailing read aligners, such as BWA-MEM and Bowtie 2, use the S-W algorithm to implement the seed-and-extend paradigm. In this work, we further extend the functionality of the S-W algorithm to evaluate the similarity between a pair of sequences without going through traceback process, and design a three-level hardware scoring system to compute final result efficiently. The system is made reconfigurable to align pairs of sequences of various length with a restriction of maximum number of errors. Experimental results show that the system can achieve a throughput of 685Mb/s at 69 iterations in the case of 126bp and the accuracy rate of the outputs is over 98% campared with software results. To the best of our knowledge, this is the first hardware implementation for a similarity evaluation system based on the S-W algorithm.