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异构机群上高效可扩展的Motif发现并行算法
引用本文:李锦,钟诚.异构机群上高效可扩展的Motif发现并行算法[J].计算机科学,2012,39(3):279-282.
作者姓名:李锦  钟诚
作者单位:(广西大学计算机与电子信息学院 南宁 530004)
基金项目:国家自然科学基金(60563003);广西大学拔尖创新团队建设计划(211-3-1-45)资助
摘    要:在节点具有不同计算速度、不同通信能力的异构机群系统上,分别建立求解l≤16和l>16的Motif发现问题的最优序列分配模型,在此基础上设计实现融合投票和统一投影-邻居阈值思想的Motif发现并行算法。实验结果表明,给出的基于最优序列分配策略的Motif发现并行算法具有良好的加速和可扩展性,优于采用平均分配策略的Motif发现并行算法。

关 键 词:DNA序列  Motif发现  并行算法  异构机群  数据分配模型

Efficient and Scalable Parallel Algorithm for Motif Finding on Heterogeneous Cluster Systems
LI Jin ZHONG Cheng.Efficient and Scalable Parallel Algorithm for Motif Finding on Heterogeneous Cluster Systems[J].Computer Science,2012,39(3):279-282.
Authors:LI Jin ZHONG Cheng
Affiliation:LI Jin ZHONG Cheng(School of Computer and Electronics and Information,Guangxi University,Nanning 530004,China)
Abstract:The optimal sequence distribution models for solving Motif finding with length l≤16 and l>16 were cons-tructed respectively and a parallel algorithm to find Motif combining voting algorithm with uniform projection and neighbourhood thresholding algorithm was implemented on the heterogeneous cluster that the processor nodes have different computing speed and distinct communication capability.Experimental results show that the parallel Motif finding algorithm using optimal sequence distribution strategy has good speedup and scalability,and it is superior to the parallel algorithm using even distribution strategy.
Keywords:DNA sequence  Motif finding  Parallel algorithm  Heterogeneous clusters  Data distribution model
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