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Multiple biological sequence alignment in heterogeneous multicore clusters with user-selectable task allocation policies

机译:具有用户可选任务分配策略的异构多核集群中的多个生物序列比对

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Multiple Sequence Alignment (MSA) is an important problem in Bioin-formatics that aims to align more than two sequences in order to emphasize similarity regions. This problem is known to be NP-Hard, so heuristic methods are used to solve it. DIALIGN-TX is an iterative heuristic method for MSA that generates alignments by concatenating ungapped regions with high similarity. Usually, the first phase of MSA algorithms is parallelized by distributing several independent tasks among the nodes. Even though heterogeneous multicore clusters are becoming very common nowadays, very few task allocation policies were proposed for this type of architecture. This paper proposes an MPI/OpenMP master/slave parallel strategy to run DIALIGN-TX in heterogeneous multicore clusters, with several allocation policies. We show that an appropriate choice of the master node has great impact on the overall system performance. Also, the results obtained in a heterogeneous multicore cluster composed of 4 nodes (30 cores), with real sequence sets show that the execution time can be drastically reduced when the appropriate allocation policy is used.
机译:多序列比对(MSA)是生物信息学中的一个重要问题,其目的是比对两个以上的序列以强调相似性区域。已知此问题是NP-Hard,因此使用启发式方法来解决它。 DIALIGN-TX是一种用于MSA的迭代启发式方法,该方法通过将具有高度相似性的未插入区域连接起来来生成比对。通常,通过在节点之间分配几个独立的任务来并行化MSA算法的第一阶段。尽管异构多核集群如今变得非常普遍,但针对这种类型的体系结构却很少提出任务分配策略。本文提出了一种MPI / OpenMP主/从并行策略,可在具有多种分配策略的异构多核群集中运行DIALIGN-TX。我们表明,适当选择主节点会对整体系统性能产生很大影响。同样,在由4个节点(30个核心)组成的异构多核群集中获得的结果以及真实的序列集表明,当使用适当的分配策略时,可以大大减少执行时间。

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