科研之友
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摘要
Multiple sequence alignment (MSA) is one of the most important problems in computational biology. As availability of genomic and proteomic data constantly increases, new tools for processing this data in reasonable time are needed. One method of addressing this issue is parallelization. Nowadays, graphical processing units offer much more computational power than central processors, hence CPUs become more and more popular in computational-intensive tasks, including sequence alignment. We investigate the constrained multiple sequence alignment problem (CMSA) which allows some prior knowledge to be introduced to a final alignment. As a result we propose a GPU-parallel version of the Center Star algorithm which overtakes vastly its CPU-serial equivalent as well as the parallel version run on the quad-core processor. The speedups over CPU-serial algorithm were from 30 to 110 in the case of synthetic sets and from 55 to 75 for the real sequences obtained from the Pfam database.
- 出版日期2012-6
