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在图形处理单元上进行的单精度开壳层耦合簇单双激发(CCSD)和耦合簇单双激发加微扰三重激发(CCSD(T))计算。

Single-precision open-shell CCSD and CCSD(T) calculations on graphics processing units.

作者信息

Wang Zhifan, Guo Minggang, Wang Fan

机构信息

College of Chemistry and Life Science/Sichuan Provincial Key Laboratory for Structural Optimization and Application of Functional Molecules, Chengdu Normal University, Chengdu, 611130, P. R. China.

出版信息

Phys Chem Chem Phys. 2020 Nov 21;22(43):25103-25111. doi: 10.1039/d0cp03800h. Epub 2020 Oct 29.

Abstract

It has been shown that coupled-cluster calculations with single-precision data are able to provide correlation energy with insignificant loss of accuracy. In this work, we employed consumer GPUs to accelerate open-shell spin-unrestricted CCSD and CCSD(T) calculations based on single-precision data. Some open-shell molecules are calculated to benchmark the acceleration performance of GPUs. In CCSD calculations, good acceleration performance on consumer GPUs is achieved for molecules when all the two-electron integrals can be saved in the host memory. On the other hand, I/O operations cost a lot of time for larger molecules and the performance of GPUs is not as significant. Good acceleration performance can usually be obtained in calculating the (T) correction employing GPUs since matrix contractions are always more costly than other operations. For systems with less than four hundred basis functions, our single-precision GPU code could provide an acceleration of 4-14 times for CCSD calculations and 12-20 times for (T) correction compared with double-precision CPU codes on the same hardware level.

摘要

研究表明,使用单精度数据的耦合簇计算能够提供相关能,且精度损失可忽略不计。在本工作中,我们使用消费级图形处理器(GPU)来加速基于单精度数据的开壳层自旋非限制耦合簇单双激发(CCSD)和CCSD(T)计算。通过计算一些开壳层分子来评估GPU的加速性能。在CCSD计算中,当所有双电子积分都能保存在主机内存中时,消费级GPU对分子具有良好的加速性能。另一方面,对于较大的分子,输入/输出操作会花费大量时间,GPU的性能就不那么显著了。由于矩阵收缩通常比其他操作成本更高,因此在使用GPU计算(T)校正时通常可以获得良好的加速性能。对于基函数少于四百个的系统,与相同硬件水平下的双精度中央处理器(CPU)代码相比,我们的单精度GPU代码在CCSD计算中可提供4至14倍的加速,在(T)校正中可提供12至20倍的加速。

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