基于gpu的云计算,比较蛋白质结合位点的结构

M. Leinweber, Lars Baumgärtner, Marco Mernberger, T. Fober, E. Hüllermeier, G. Klebe, Bernd Freisleben
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引用次数: 13

摘要

在本文中,我们提出了一种使用基于gpu的云计算基础设施来有效地执行蛋白质结合位点的结构比较的新方法。最近基于图形的算法SEGA的原始基于cpu的Java版本已经在OpenCL中重写,以便在一组Amazon EC2集群GPU实例上并行运行NVIDIA GPU。这种SEGA的新实现已经在CavBase中包含的蛋白质结构数据子集上进行了测试,提供了比以往文献中报道的更大规模的蛋白质结合位点的结构比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GPU-based Cloud computing for comparing the structure of protein binding sites
In this paper, we present a novel approach for using a GPU-based Cloud computing infrastructure to efficiently perform a structural comparison of protein binding sites. The original CPU-based Java version of a recent graph-based algorithm called SEGA has been rewritten in OpenCL to run on NVIDIA GPUs in parallel on a set of Amazon EC2 Cluster GPU Instances. This new implementation of SEGA has been tested on a subset of protein structure data contained in the CavBase, providing a structural comparison of protein binding sites on a much larger scale than in previous research efforts reported in the literature.
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