KSSOLV-GPU: An efficient GPU-enabled MATLAB toolbox for solving the Kohn-Sham equations within density functional theory in plane-wave basis set

被引:10
作者
Zhang, Zhen-lin
Jiao, Shi-zhe
Li, Jie-lan
Wu, Wen-tiao
Wan, Ling-yun
Qin, Xin-ming
Hu, Wei [1 ]
Yang, Jin-long
机构
[1] Univ Sci & Technol China, Synerget Innovat Ctr Quantum Informat & Quantum P, Hefei Natl Lab Phys Sci Microscale, Dept Chem Phys, Hefei 230026, Peoples R China
基金
中国国家自然科学基金;
关键词
Kohn-Sham Solver; Density functional theory; Iterative eigensolver; MATLAB; GPU; MOLECULAR-DYNAMICS; EXCHANGE; APPROXIMATION; ADSORPTION; SOFTWARE; STATE; CODE;
D O I
10.1063/1674-0068/cjcp2108139
中图分类号
O64 [物理化学(理论化学)、化学物理学]; O56 [分子物理学、原子物理学];
学科分类号
070203 ; 070304 ; 081704 ; 1406 ;
摘要
KSSOLV (Kohn-Sham Solver) is a MATLAB (Matrix Laboratory) tool-box for solving the Kohn-Sham density functional theory (KS-DFT) with the plane-wave basis set. In the KS-DFT calculations, the most expensive part is commonly the diagonalization of Kohn-Sham Hamiltonian in the self-consistent field (SCF) scheme. To enable a personal computer to perform medium-sized KS-DFT calculations that contain hundreds of atoms, we present a hybrid CPU-GPU implementation to accelerate the iterative diagonalization algorithms implemented in KSSOLV by using the MATLAB built-in Parallel Computing Toolbox. We compare the performance of KSSOLV-GPU on three types of GPU, including RTX3090, V100, and A100, with conventional CPU implementation of KSSOLV respectively and numerical results demonstrate that hybrid CPU-GPU implementation can achieve a speedup of about 10 times compared with sequential CPU calculations for bulk silicon systems containing up to 128 atoms.
引用
收藏
页码:552 / 564
页数:13
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