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GPU‐Accelerated Large‐Scale Excited‐State Simulation Based on Divide‐and‐Conquer Time‐Dependent Density‐Functional Tight‐Binding
Author(s) -
Yoshikawa Takeshi,
Komoto Nana,
Nishimura Yoshifumi,
Nakai Hiromi
Publication year - 2019
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.26053
Subject(s) - computer science , tight binding , divide and conquer algorithms , linear scale , computational science , central processing unit , excited state , scaling , density functional theory , code (set theory) , intramolecular force , parallel computing , algorithm , electronic structure , physics , chemistry , computational chemistry , computer hardware , atomic physics , quantum mechanics , mathematics , geometry , geodesy , set (abstract data type) , programming language , geography
The present study implemented the divide‐and‐conquer time‐dependent density‐functional tight‐binding (DC‐TDDFTB) code on a graphical processing unit (GPU). The DC method, which is a linear‐scaling scheme, divides a total system into several fragments. By separately solving local equations in individual fragments, the DC method could reduce slow central processing unit (CPU)‐GPU memory access, as well as computational cost, and avoid shortfalls of GPU memory. Numerical applications confirmed that the present code on GPU significantly accelerated the TDDFTB calculations, while maintaining accuracy. Furthermore, the DC‐TDDFTB simulation of 2‐acetylindan‐1,3‐dione displays excited‐state intramolecular proton transfer and provides reasonable absorption and fluorescence energies with the corresponding experimental values. © 2019 Wiley Periodicals, Inc.