4.7 Article

A spectrum slicing method for the Kohn-Sham problem

Journal

COMPUTER PHYSICS COMMUNICATIONS
Volume 183, Issue 3, Pages 497-505

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.cpc.2011.11.005

Keywords

Spectrum slicing; Hermitian eigenproblem; Kohn-Sham equation; Sparse parallel eigensolver; Polynomial filtering

Funding

  1. National Science Foundation [DMR-0941645, OCI-1047997]
  2. Welch Foundation [F-1708]
  3. Office of Science of the U.S. Department of Energy [DE-AC02-05CH11231, DE-AC05-00OR22725]
  4. National Science Foundation through TeraGrid at the Texas Advanced Computing Center (TACC) [TG-DMR090026]
  5. Direct For Computer & Info Scie & Enginr
  6. Office of Advanced Cyberinfrastructure (OAC) [1047997] Funding Source: National Science Foundation
  7. Division Of Materials Research
  8. Direct For Mathematical & Physical Scien [0941645] Funding Source: National Science Foundation
  9. Office of Advanced Cyberinfrastructure (OAC)
  10. Direct For Computer & Info Scie & Enginr [1047961] Funding Source: National Science Foundation

Ask authors/readers for more resources

Solving the Kohn-Sham equation, which arises in density functional theory, is a standard procedure to determine the electronic structure of atoms, molecules, and condensed matter systems. The solution of this nonlinear eigenproblem is used to predict the spatial and energetic distribution of electronic states. However, obtaining a solution for large systems is computationally intensive because the problem scales super-linearly with the number of atoms. Here we demonstrate a divide and conquer method that partitions the necessary eigenvalue spectrum into slices and computes each partial spectrum on an independent group of processors in parallel. We focus on the elements of the spectrum slicing method that are essential to its correctness and robustness such as the choice of filter polynomial, the stopping criterion for a vector iteration, and the detection of duplicate eigenpairs computed in adjacent spectral slices. Some of the more prominent aspects of developing an optimized implementation are discussed. (C) 2011 Elsevier B.V. All rights reserved.

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