Acceleration of a parallel homology search for base sequences by a GPU

In biology, there is a research field `bioinformatics' in which computers are used as a method for problem solving. Bioinformatics includes a topic that is related to the analysis of genetic information. To analyze genetic information, a homology search is used. The homology search detects similar parts of two base sequences. The Smith-Waterman algorithm is one of the most famous approaches for a homology search. The algorithm is sometimes executed in parallel by using a GPU. In this paper, we propose an acceleration method of a parallel homology search based on the Smith-Waterman algorithm by using a GPU. The proposed method first reduces the range of calculation of the Smith-Waterman algorithm by preprocess. Next, it applies the Smith-Waterman algorithm in parallel to the multiple sub matrices obtained after the preprocess to improve efficiency. As a result of an evaluation experiment, we have measured that our method gained at most 3.8 times in execution speed compared to a simple parallel execution of the Smith-Waterman algorithm by a GPU. The gain is caused by reduction of the calculation of the Smith-Waterman algorithm and by detecting sub sequences that can be executed asynchronously in parallel.