High Performance Protein Sequence Database Scanning on the Cell Broadband Engine
Author(s) -
Adrianto Wirawan,
Bertil Schmidt,
Huiliang Zhang,
Chee Keong Kwoh
Publication year - 2009
Publication title -
scientific programming
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.269
H-Index - 36
eISSN - 1875-919X
pISSN - 1058-9244
DOI - 10.1155/2009/615038
Subject(s) - computer science , implementation , parallel computing , heuristic , multi core processor , sequence (biology) , broadband , smith–waterman algorithm , dynamic programming , supercomputer , sequence alignment , algorithm , artificial intelligence , programming language , telecommunications , biochemistry , chemistry , biology , gene , peptide sequence , genetics
The enormous growth of biological sequence databases has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing rapidly as well. The recent emergence of low cost parallel multicore accelerator technologies has made it possible to reduce execution times of many bioinformatics applications. In this paper, we demonstrate how the Cell Broadband Engine can be used as a computational platform to accelerate two approaches for protein sequence database scanning: exhaustive and heuristic. We present efficient parallelization techniques for two representative algorithms: the dynamic programming based Smith–Waterman algorithm and the popular BLASTP heuristic. Their implementation on a Playstation®3 leads to significant runtime savings compared to corresponding sequential implementations.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom