Parallel implementation and performance characterization of MUSCLE

Authors:
Xi Deng;Eric Li;Jiulong Shan;Wenguang Chen
Affiliations:
Tsinghua University, Dept. of Computer Science, Beijing, China;Intel China Research Center Ltd., Beijing, China;Intel China Research Center Ltd., Beijing, China;Tsinghua University, Dept. of Computer Science, Beijing, China
Venue:
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Year:
2006

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Abstract

Multiple sequence alignment is a fundamental and very computationally intensive task in molecular biology. MUSCLE, a new algorithm for creating multiple alignments of protein sequences, achieves a highest rank in accuracy and the fastest speed compared to ClustalW as well as T-Coffee, some widely used tools in multiple sequence alignment. To further accelerate the computations, we present the parallel implementation of MUSCLE in this paper. It is decomposed into several independent modules, which are parallelized with different OpenMP paradigms. We also conduct detailed performance characterization on symmetric multiple processor systems. The experiments show that MUSCLE scales well with the increase of processors, and achieves up to 15.x speedup on 16-way shared memory multiple processor system.