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Abstract
Motivation: The only algorithm guaranteed to find the optimal local alignment is the Smith–Waterman. It is also one of the slowest due to the number of computations required for the search. To speed up the algorithm, Single-Instruction Multiple-Data (SIMD) instructions have been used to parallelize the algorithm at the instruction level. Results: A faster implementation of the Smith–Waterman algorithm is presented. This algorithm achieved 2–8 times performance improvement over other SIMD based Smith–Waterman implementations. On a 2.0 GHz Xeon Core 2 Duo processor, speeds of >3.0 billion cell updates/s were achieved. Availability:Author Webpage Contact:farrar.michael@gmail.com

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