Recent implementations, applications, and extensions of the Locally Optimal Block Preconditioned Conjugate Gradient method (LOBPCG)
Numerical Analysis
2017-08-29 v1 Numerical Analysis
Computation
Abstract
Since introduction [A. Knyazev, Toward the optimal preconditioned eigensolver: Locally optimal block preconditioned conjugate gradient method, SISC (2001) DOI:10.1137/S1064827500366124] and efficient parallel implementation [A. Knyazev et al., Block locally optimal preconditioned eigenvalue xolvers (BLOPEX) in HYPRE and PETSc, SISC (2007) DOI:10.1137/060661624], LOBPCG has been used is a wide range of applications in mechanics, material sciences, and data sciences. We review its recent implementations and applications, as well as extensions of the local optimality idea beyond standard eigenvalue problems.
Keywords
Cite
@article{arxiv.1708.08354,
title = {Recent implementations, applications, and extensions of the Locally Optimal Block Preconditioned Conjugate Gradient method (LOBPCG)},
author = {Andrew Knyazev},
journal= {arXiv preprint arXiv:1708.08354},
year = {2017}
}
Comments
4 pages. Householder Symposium on Numerical Linear Algebra, June 2017