SW#–GPU-enabled exact alignments on genome scale | Zendy

Matija Korpar | Zendy; Mile Šikić | Zendy

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SW#–GPU-enabled exact alignments on genome scale

Author(s) -

Matija Korpar,

Mile Šikić

Publication year - 2013

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btt410

Subject(s) - cuda , computer science , parallel computing , smith–waterman algorithm , software , implementation , code (set theory) , dynamic programming , scale (ratio) , sequence (biology) , source code , sequence alignment , algorithm , programming language , set (abstract data type) , biochemistry , chemistry , physics , quantum mechanics , peptide sequence , gene , genetics , biology

We propose SW#, a new CUDA graphical processor unit-enabled and memory-efficient implementation of dynamic programming algorithm, for local alignment. It can be used as either a stand-alone application or a library. Although there are other graphical processor unit implementations of the Smith-Waterman algorithm, SW# is the only one publicly available that can produce sequence alignments on genome-wide scale. For long sequences, it is at least a few hundred times faster than a CPU version of the same algorithm.

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