Research on Genetic and Simulated Annealing Algorithm for Multiple Sequence Alignment Based on Hybrid Parallel Computation

被引：0
|
作者：
Li, Longsheng [1 ]
Liu, Yu [1 ]
机构：
[1] Guilin Univ Technol, Coll Informat Sci & Engn, Guilin 541004, Guangxi, Peoples R China
来源：
PROCEEDINGS OF THE 2017 2ND INTERNATIONAL CONFERENCE ON AUTOMATION, MECHANICAL AND ELECTRICAL ENGINEERING (AMEE 2017) | 2017年 / 87卷
基金：
中国国家自然科学基金;
关键词：
MOC(MPI; OpenMP; CUDA); hybrid parallel; genetic annealing; sequence alignment;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
For the computational efficiency issues of multiple sequence alignment (MSA) caused by large amount of calculation. Based on the Hybrid Parallel model for MPI, OpenMP, CUDA, research on genetic and simulated annealing algorithm for multiple sequence alignment, to maximize computing capabilities is proposed. Analyzes the GSA-MSA algorithm for Implementation principle and characteristics of the serial algorithm, and excavates potential multi-level parallelism. To design and implement comprehensive multi-level parallel for the algorithm in a variety of hybrid parallel model, respectively designed the hybrid parallel algorithms MPI+OpenMP+CUDA within multiple nodes. Experimental results show that the hybrid parallel GSA-MSA algorithm has good speedup with keeping the sensitivity for serial algorithm.
引用
收藏
页码：205 / 208
页数：4
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