三维构象蛋白质结构预测的大规模并行化应用

P. LoCascio, K. Yue, P. Cummings, K. Dill
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引用次数: 0

摘要

我们在这里提出了一个大规模科学应用的设计策略和性能分析,用于预测三维蛋白质结构。将研究的独特挑战是通过并行化过程减少时钟运行时间的主要目标,以及能够在许多非连续的超级计算机时间内可靠地运行和扩展到大规模并行配置(目前是Intel Paragon的1024个节点)的应用程序的生产。通过使用MPI作为并行软件层,可以为许多不同的并行体系结构(包括CRAY T3E和IBM SP2)重新配置足够的灵活性。应用程序,GEOCORE,预测从氨基酸序列的天然肽构象的小集合。GEOCORE使用非常简单的能量函数和广泛的构象搜索过程。该序列程序已在大约20个小肽上进行了测试,并证明能够区分原生和非原生结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Large Scale Parallelization of a Conformational 3D Protein Structure Prediction Application
We present here the design strategy and performance analysis of a large scale scientific application, for the prediction of 3D Protein structures. The unique challenges which will be investigated are the primary objectives of a reduction in wall clock run time through the parallelization process, and the production of an application capable of running and scaling to a massively parallel configuration (currently 1024 nodes of the Intel Paragon) reliably for many non-contiguous days of supercomputer time. Enough flexibility to be reconfigured for a number of different parallel architectures including the CRAY T3E and IBM SP2 was included through the use of MPI as the parallel software layer. The application, GEOCORE, predicts small ensembles of native-like peptide conformations from amino acid sequences. GEOCORE uses a very simple energy function and an extensive conformational search process. The serial program has been tested on around 20 small peptides and is shown to be capable of discriminating native from non-native structures.
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