High performance in silico virtual drug screening on many-core processors.
High performance in silico virtual drug screening on many-core processors.
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DOI：
10.1177/1094342014528252
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发表时间：
2015-05
期刊：
影响因子：
--
通讯作者：
Ibarra AA
中科院分区：
文献类型：
--
作者：
McIntosh-Smith S;Price J;Sessions RB;Ibarra AA
药物筛选是制药行业药物开发管道的重要组成部分。传统的基于实验室的方法越来越多地被计算方法所增强，从简单的分子相似性搜索到更复杂的药效团匹配，再到计算密集型的方法，如分子对接。后者模拟药物分子与其靶标（通常是蛋白质分子）的结合。在这项工作中，我们描述BUDE，布里斯托大学对接引擎，它已被移植到OpenCL行业标准的并行编程语言，以利用现代众核处理器的性能。我们高度优化的BUDE OpenCL实现在单个Nvidia GTX 680 GPU上保持1.43 TFLOP/s，或峰值性能的46%。BUDE还利用OpenCL在来自不同供应商的各种不同计算机架构上提供有效的性能可移植性，包括Nvidia和AMD的GPU、英特尔的Xeon Phi和具有SIMD指令集的多核CPU。
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.
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