Parallel self-consistent-field calculations via Chebyshev-filtered subspace acceleration

Yunkai Zhou, Yousef Saad, Murilo L. Tiago, and James R. Chelikowsky
Phys. Rev. E 74, 066704 – Published 28 December 2006

Abstract

Solving the Kohn-Sham eigenvalue problem constitutes the most computationally expensive part in self-consistent density functional theory (DFT) calculations. In a previous paper, we have proposed a nonlinear Chebyshev-filtered subspace iteration method, which avoids computing explicit eigenvectors except at the first self-consistent-field (SCF) iteration. The method may be viewed as an approach to solve the original nonlinear Kohn-Sham equation by a nonlinear subspace iteration technique, without emphasizing the intermediate linearized Kohn-Sham eigenvalue problems. It reaches self-consistency within a similar number of SCF iterations as eigensolver-based approaches. However, replacing the standard diagonalization at each SCF iteration by a Chebyshev subspace filtering step results in a significant speedup over methods based on standard diagonalization. Here, we discuss an approach for implementing this method in multi-processor, parallel environment. Numerical results are presented to show that the method enables to perform a class of highly challenging DFT calculations that were not feasible before.

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  • Received 31 May 2006

DOI:https://doi.org/10.1103/PhysRevE.74.066704

©2006 American Physical Society

Authors & Affiliations

Yunkai Zhou1,*, Yousef Saad2, Murilo L. Tiago3, and James R. Chelikowsky3,4

  • 1Department of Mathematics, Southern Methodist University, Dallas, Texas 75275, USA
  • 2Department of Computer Science & Engineering, University of Minnesota, Minneapolis, Minnesota 55455, USA
  • 3Center for Computational Materials, Institute for Computational Engineering and Sciences, University of Texas, Austin, Texas 78712, USA
  • 4Departments of Physics and Chemical Engineering, University of Texas, Austin, Texas 78712, USA

  • *Email address: yzhou@smu.edu

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Issue

Vol. 74, Iss. 6 — December 2006

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