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利用图形处理单元加速量子化学计算——迈向高密度虚拟药物发现

Accelerating quantum chemistry calculations with graphical processing units - toward in high-density (HD) silico drug discovery.

作者信息

Hagiwara Yohsuke, Ohno Kazuki, Orita Masaya, Koga Ryota, Endo Toshio, Akiyama Yutaka, Sekijima Masakazu

机构信息

Drug Discovery Research, Astellas Pharma Inc., 21 Miyukigaoka, Tsukuba, Ibaraki, 305-8585, Japan.

出版信息

Curr Comput Aided Drug Des. 2013 Sep;9(3):396-401. doi: 10.2174/15734099113099990031.

Abstract

The growing power of central processing units (CPU) has made it possible to use quantum mechanical (QM) calculations for in silico drug discovery. However, limited CPU power makes large-scale in silico screening such as virtual screening with QM calculations a challenge. Recently, general-purpose computing on graphics processing units (GPGPU) has offered an alternative, because of its significantly accelerated computational time over CPU. Here, we review a GPGPU-based supercomputer, TSUBAME2.0, and its promise for next generation in silico drug discovery, in high-density (HD) silico drug discovery.

摘要

中央处理器(CPU)计算能力的不断提升使得利用量子力学(QM)计算进行计算机辅助药物发现成为可能。然而,有限的CPU能力使得大规模计算机辅助筛选,如基于QM计算的虚拟筛选成为一项挑战。近来,基于图形处理器的通用计算(GPGPU)因其相比CPU显著加速的计算时间提供了一种替代方案。在此,我们综述了基于GPGPU的超级计算机TSUBAME2.0及其在下一代计算机辅助药物发现、高密度(HD)计算机辅助药物发现中的前景。

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