Efficient Shift-and-Invert Preconditioning for Multi-GPU Accelerated Density Functional Calculations

Citations

WEB OF SCIENCE

2
Citations

SCOPUS

2

초록

To accelerate the iterative diagonalization of electronic structure calculations, we propose a new inexact shift-and-invert (ISI) preconditioning method. The key idea is to improve shift values in the ISI preconditioning to be closer to the exact eigenvalues, leading to a significant boost in the convergence speed of the iterative diagonalization. Furthermore, we adopted a preconditioned conjugate gradient solver to rapidly evaluate an inversion process. Finally, we accelerated overall processes, including the proposed modification, with state-of-the-art graphical processing units (GPUs) and assessed its parallel efficiency with real-space density functional calculations of 1D, 2D, and 3D periodic systems. Our method attains both fast diagonalization convergence and high multi-GPU parallel efficiency. This is evident from the fact that single-point density functional calculations for hundreds of atom systems can be done in approximately 10 s using 8 GPUs. The proposed method can be generally applied to any electronic structure calculation methods involving large-scale diagonalizations.

키워드

EIGENVALUE PROBLEMSDIAGONALIZATIONMATRIXLANCZOSOPTIMIZATIONCONVERGENCEEIGENSOLVERALGORITHM
제목
Efficient Shift-and-Invert Preconditioning for Multi-GPU Accelerated Density Functional Calculations
저자
Woo, JeheonKim, Woo YounChoi, Sunghwan
DOI
10.1021/acs.jctc.4c00721
발행일
2024-08-27
유형
Article
저널명
Journal of Chemical Theory and Computation
20
17
페이지
7443 ~ 7452