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在多核处理器上进行高性能虚拟药物筛选。

High performance virtual drug screening on many-core processors.

作者信息

McIntosh-Smith Simon, Price James, Sessions Richard B, Ibarra Amaurys A

机构信息

Department of Computer Science, University of Bristol, Bristol, UK.

School of Biochemistry, University of Bristol, Bristol, UK.

出版信息

Int J High Perform Comput Appl. 2015 May;29(2):119-134. doi: 10.1177/1094342014528252.

Abstract

Drug screening is an important part of the drug development pipeline for the pharmaceutical industry. Traditional, lab-based methods are increasingly being augmented with computational methods, ranging from simple molecular similarity searches through more complex pharmacophore matching to more computationally intensive approaches, such as molecular docking. The latter simulates the binding of drug molecules to their targets, typically protein molecules. In this work, we describe BUDE, the Bristol University Docking Engine, which has been ported to the OpenCL industry standard parallel programming language in order to exploit the performance of modern many-core processors. Our highly optimized OpenCL implementation of BUDE sustains 1.43 TFLOP/s on a single Nvidia GTX 680 GPU, or 46% of peak performance. BUDE also exploits OpenCL to deliver effective performance portability across a broad spectrum of different computer architectures from different vendors, including GPUs from Nvidia and AMD, Intel's Xeon Phi and multi-core CPUs with SIMD instruction sets.

摘要

药物筛选是制药行业药物研发流程的重要组成部分。传统的基于实验室的方法越来越多地被计算方法所补充,从简单的分子相似性搜索到更复杂的药效团匹配,再到计算量更大的方法,如分子对接。后者模拟药物分子与其靶点(通常是蛋白质分子)的结合。在这项工作中,我们描述了布里斯托大学对接引擎(BUDE),它已被移植到OpenCL行业标准并行编程语言中,以利用现代多核处理器的性能。我们对BUDE进行了高度优化的OpenCL实现,在单个英伟达GTX 680 GPU上可维持1.43万亿次浮点运算每秒的速度,即峰值性能的46%。BUDE还利用OpenCL在来自不同供应商的广泛不同计算机架构上实现有效的性能可移植性,包括英伟达和AMD的GPU、英特尔的至强融核以及具有SIMD指令集的多核CPU。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ae/4425459/5bd86f050b4f/10.1177_1094342014528252-fig1.jpg

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