Parallel Cache Efficient Algorithm and Implementation of Needleman-Wunsch Global Sequence Alignment
An approach allowing us to improve the locality of a parallel Needleman-Wunsch (NW) global sequence alignment algorithm is proposed. The original NW algorithm works with an arbitrary gap penalty function and examines all possible gap lengths. To compute the score of an element of an NW array, cells gap symbols are looked back over entire row and column as well as one adjacent cell. We modified the NW algorithm so to read cells only with the row-major order by means of forming a copy of the transposed scoring array. The loop skewing technique is used to generate parallel code. A formal parallel NW algorithm is presented. Experimental results demonstrate super-linear speed-up factor of the accelerated code due to considerable increasing code locality on a studied modern multi-core platform.
KeywordsNeedleman-Wunsch algorithm Global sequence alignment Cache efficiency Loop skewing Bioinformatics
Thanks to the Miclab Team (miclab.pl) from the Technical University of Czestochowa (Poland) that provided access to high performance multi-core machines for the experimental study presented in this paper.
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