首页> 外文期刊>International Journal of Distributed and Parallel Systems >Fine Grain Parallel Construction of Neighbour-joining Phylogenetic Trees with Reduced Redundancy Using Multithreading
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Fine Grain Parallel Construction of Neighbour-joining Phylogenetic Trees with Reduced Redundancy Using Multithreading

机译:使用多线程的减少冗余的邻域系统进化树的细粒度并行构建

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In biological research, scientists often need to use the information of the species to infer the evolutionary relationship among them. The evolutionary relationships are generally represented by a labeled binary tree, called the evolutionary tree (or phylogenetic tree). The phylogeny problem is computationally intensive, and thus it is suitable for parallel computing environment. In this paper, a fast algorithm for constructing Neighbor-Joining phylogenetic trees has been developed. The CPU time is drastically reduced as compared with sequential algorithms. The new algorithm includes three techniques: Firstly, a linear array A[N] is introduced to store the sum of every row of the distance matrix (the same as SK), which can eliminate many repeated (redundancy) computations, and the value of A[i] are computed only once at the beginning of the algorithm, and are updated by three elements in the iteration. Secondly, a very compact formula for the sum of all the branch lengths of OTUs (Operational Taxonomic Units) i and j has been designed. Thirdly, multiple parallel threads are used for computation of nearest neighboring pair.
机译:在生物学研究中,科学家经常需要利用物种的信息来推断它们之间的进化关系。进化关系通常由标记的二叉树表示,称为进化树(或系统树)。系统发生问题是计算密集型的,因此适合并行计算环境。本文提出了一种构建邻居结合系统发生树的快速算法。与顺序算法相比,CPU时间大大减少。新算法包括三种技术:首先,引入线性数组A [N]来存储距离矩阵的每一行的总和(与SK相同),这可以消除许多重复的(冗余)计算,以及A [i]在算法开始时仅计算一次,并在迭代中由三个元素更新。其次,为OTU(操作分类单元)i和j的所有分支长度之和设计了一个非常紧凑的公式。第三,使用多个并行线程来计算最近的相邻对。

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