Parallel processing in biological sequence comparison using general purpose processors

The comparison and alignment of DNA and protein sequences are important tasks in molecular biology and bioinformatics. One of the most well known algorithms to perform the string-matching operation present in these tasks is the Smith-Waterman algorithm (SW). However, it is a computation intensive algorithm, and many researchers have developed heuristic strategies to avoid using it, specially when using large databases to perform the search. There are several efficient implementations of the SW algorithm on general purpose processors. These implementations try to extract data-level parallelism taking advantage of single-instruction multiple-data extensions (SIMD), capable of performing several operations in parallel on a set of data. In this paper, we propose a more efficient data parallel implementation of the SW algorithm. Our proposed implementation obtains a 30% reduction in the execution time relative to the previous best data-parallel alternative. In this paper we review different alternative implementation of the SW algorithm, compare them with our proposal, and present preliminary results for some heuristic implementations. Finally, we present a detailed study of the computational complexity of the different alignment algorithms presented and their behavior on the different aspect of the CPU microarchitecture.