QRCODE: Massively parallelized real-time time-dependent density functional theory for periodic systems

被引:0
|
作者
Choi, Min [1 ]
Okyay, Mahmut Sait [1 ]
Dieguez, Adrian Perez [2 ]
Del Ben, Mauro [2 ]
Ibrahim, Khaled Z. [2 ]
Wong, Bryan M. [1 ]
机构
[1] Univ Calif Riverside, Dept Chem & Environm Engn, Dept Phys & Astron, Mat Sci & Engn Program, Riverside, CA 92521 USA
[2] Lawrence Berkeley Natl Lab, Appl Math & Computat Res Div, Berkeley, CA 94720 USA
关键词
Real-time time-dependent density functional; theory; Massive parallelization; Periodic systems; Electron dynamics; Quantum dynamics; Harmonic generation; HIGH HARMONIC-GENERATION; 2ND-HARMONIC GENERATION; DYNAMICS; IMPLEMENTATION; SIMULATION; EFFICIENT; OCTOPUS; TOOL;
D O I
10.1016/j.cpc.2024.109349
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We present a new software module, QRCODE (Quantum Research for Calculating Optically Driven Excitations), for massively parallelized real-time time-dependent density functional theory (RT-TDDFT) calculations of periodic systems in the open-source Qbox software package. Our approach utilizes a custom implementation of a fast Fourier transformation scheme that significantly reduces inter-node message passing interface (MPI) communication of the major computational kernel and shows impressive scaling up to 16,344 CPU cores. In addition to improving computational performance, QRCODE contains a suite of various time propagators for accurate RTTDDFT calculations. As benchmark applications of QRCODE, we calculate the current density and optical absorption spectra of hexagonal boron nitride (h-BN) and photo-driven reaction dynamics of the ozone-oxygen reaction. We also calculate the second and higher harmonic generation of monolayer and multi-layer boron nitride structures as examples of large material systems. Our optimized implementation of RT-TDDFT in QRCODE enables large-scale calculations of real-time electron dynamics of chemical and material systems with enhanced computational performance and impressive scaling across several thousand CPU cores.
引用
收藏
页数:9
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