Performance Evaluation of Protein Structure Comparison Algorithms Under Integrated Resource Management Environment for MPI Jobs

A. Shah, Daniel Barthel, G. Folino, N. Krasnogor
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引用次数: 0

Abstract

The comparison of protein tertiary structures is a key milestone in many structural bioinformatics activities that rely in comparing very large structure datasets. As the number of proteins in the dataset increases, the corresponding computational time taken by the protein structure comparison algorithms also increases, squarely for an all-against-all comparison and linearly for an all-against-target assessment. Thus ever larger proteomics problems call for the distribution of pairwise comparison jobs in the form of well granulated subsets/packages to be run in parallel on a pool of networked processors/workstations under the coordination of a message passing interface (MPI) environment. This paper evaluates the effect on the performance of such jobs when the MPI environment is integrated with a local resource management system (LRMS) such as sun grid engine (SGE). From our experiments with different ways of integration we draw a comparative picture of all possible approaches with the description of resource usage information for each parallel job on each processor. Understanding of different ways of integration sheds light on the most promising routes for setting up an efficient environment for very large scale protein structure comparisons.
综合资源管理环境下MPI作业中蛋白质结构比较算法的性能评价
蛋白质三级结构的比较是许多结构生物信息学活动的关键里程碑,这些活动依赖于比较非常大的结构数据集。随着数据集中蛋白质数量的增加,蛋白质结构比较算法所花费的相应计算时间也会增加,对于全对全比较来说,计算时间是正数,对于全对目标评估来说,计算时间是线性的。因此,更大的蛋白质组学问题需要以良好粒度的子集/包的形式分发成对比较作业,以便在消息传递接口(MPI)环境的协调下在网络处理器/工作站池上并行运行。本文评估了MPI环境与本地资源管理系统(LRMS)(如太阳网格引擎(SGE))集成时对这些作业性能的影响。通过对不同集成方式的实验,我们通过描述每个处理器上每个并行作业的资源使用信息,绘制了所有可能方法的比较图。对不同整合方式的理解揭示了最有希望为大规模蛋白质结构比较建立有效环境的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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