GPU上药物发现过程的加速

Ajinkya R. Nikam, Akshay Nara, Deepak Paliwal, Sandip M. Walunj
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引用次数: 4

摘要

数据库的计算筛选在药物研究和开发中得到了广泛的应用。要进行这种筛选测试,使用的技术是虚拟筛选。它采用基于计算机的算法和方法,考虑了许多参数,在生物结构的基础上发现新的配体。发现新药的过程现在已成为所有制药工业的一个关键因素。虚拟筛选的加速将为节省所需的资源和时间提供优势。本文将讨论CUDA和GP-GPU并行架构对虚拟筛选加速的有效实现。在CUDA编程模型中实现。该实现试图最大限度地发挥GPU的优势,在药物发现过程中给出更好的解决方案。当在CUDA GPU架构上实现时,结果将是213x的加速,以提供更好的解决方案,考虑到性能和成本比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Acceleration of drug discovery process on GPU
Computational screening of databases have gained immense popularity in the pharmaceutical research and development. To do such screening tests the technique used is Virtual Screening. It uses computer based algorithms and methods which takes into consideration a lot of parameters to discover new ligands on the basis of biological structures. The process of discovering new drugs has now become a crucial factor for all the Pharmaceutical Industries. Acceleration of Virtual screening would provide an edge to save the resources as well as time required. Here, the effectual implementation of parallel architecture of CUDA and GP-GPU for the acceleration of Virtual screening will be discussed. The implementation is in CUDA programming models. This implementation tries to take maximum advantage of a GPU to give better solution in the process of drug discovery. The result which would be 213× speedup when implemented on CUDA GPU architecture to provide the better solution considering performance & cost ratio.
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