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用于使用MPI进行并行计算的新TNT例程。

New TNT routines for parallel computing with MPI.

作者信息

Morales Martín E, Goloboff Pablo A

机构信息

Unidad Ejecutora Lillo (Fundación Miguel Lillo - Consejo Nacional de Investigaciones Científicas y Técnicas), Miguel Lillo 251, S. M. de Tucumán 4000, Argentina.

Unidad Ejecutora Lillo (Fundación Miguel Lillo - Consejo Nacional de Investigaciones Científicas y Técnicas), Miguel Lillo 251, S. M. de Tucumán 4000, Argentina; American Museum of Natural History, Central Park West at 79th Street, New York, United States.

出版信息

Mol Phylogenet Evol. 2023 Jan;178:107643. doi: 10.1016/j.ympev.2022.107643. Epub 2022 Oct 8.

Abstract

Phylogenetic inference, which involves time-consuming calculations, is a field where parallelization can speed up the resolution of many problems. TNT (a widely used program for phylogenetic analysis under parsimony) allows parallelization under the PVM system (Parallel Virtual Machine). However, as the basic aspects of the implementation remain unpublished, few studies have taken advantage of the parallelization routines of TNT. In addition, the PVM system is deprecated by many system administrators. One of the most common standards for high performance computing is now MPI (Message Passing Interface). To facilitate the use of the parallel analyses offered by TNT, this paper describes the basic aspects of the implementation, as well as a port of the parallelization interface of TNT into MPI. The use of the new routines is illustrated by reanalysis of seven significant datasets, either recent phylogenomic datasets with many characters (up to 2,509,064 characters) or datasets with large numbers of taxa (up to 13,921 taxa). Versions of TNT including the MPI functionality are available at: http://www.lillo.org.ar/phylogeny/tnt/.

摘要

系统发育推断涉及耗时的计算,在这个领域中,并行化可以加快许多问题的解决速度。TNT(一种广泛用于简约法系统发育分析的程序)允许在PVM系统(并行虚拟机)下进行并行化。然而,由于其实现的基本方面尚未发表,很少有研究利用TNT的并行化程序。此外,许多系统管理员已不再使用PVM系统。现在,高性能计算最常用的标准之一是MPI(消息传递接口)。为了便于使用TNT提供的并行分析,本文描述了实现的基本方面,以及将TNT的并行化接口移植到MPI中的情况。通过重新分析七个重要数据集来说明新程序的使用,这些数据集要么是具有许多特征(多达2,509,064个特征)的近期系统发育基因组数据集,要么是具有大量分类单元(多达13,921个分类单元)的数据集。包含MPI功能的TNT版本可在以下网址获取:http://www.lillo.org.ar/phylogeny/tnt/

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