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An Algebraic Multilevel Preconditioner with Low-Rank Corrections for Sparse Symmetric Matrices

Journal Article · · SIAM Journal on Matrix Analysis and Applications
DOI:https://doi.org/10.1137/15m1021830· OSTI ID:1756735
 [1];  [2];  [1]
  1. Univ. of Minnesota, Twin Cities, MN (United States)
  2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

In this work, we describe a multilevel preconditioning technique for solving sparse symmetric linear systems of equations. This “Multilevel Schur Low-Rank” (MSLR) preconditioner first builds a tree structure $$\mathcal{T}$$ based on a hierarchical decomposition of the matrix and then computes an approximate inverse of the original matrix level by level. Unlike classical direct solvers, the construction of the MSLR preconditioner follows a top-down traversal of $$\mathcal{T}$$ and exploits a low-rank property that is satisfied by the difference between the inverses of the local Schur complements and specific blocks of the original matrix. A few steps of the generalized Lanczos tridiagonalization procedure are applied to capture most of this difference. Numerical results are reported to illustrate the efficiency and robustness of the MSLR preconditioner with both two- and three-dimensional discretized PDE problems and with publicly available test problems.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC52-07NA27344
OSTI ID:
1756735
Report Number(s):
LLNL-JRNL--680317; 804288
Journal Information:
SIAM Journal on Matrix Analysis and Applications, Journal Name: SIAM Journal on Matrix Analysis and Applications Journal Issue: 1 Vol. 37; ISSN 0895-4798
Publisher:
SIAMCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (2)

Multilevel approaches for FSAI preconditioning: MULTILEVEL APPROACHES FOR FSAI PRECONDITIONING
  • Magri, Victor A. P.; Franceschini, Andrea; Ferronato, Massimiliano
  • Numerical Linear Algebra with Applications, Vol. 25, Issue 5 https://doi.org/10.1002/nla.2183
journal April 2018
Parallel Multiprojection Preconditioned Methods Based on Subspace Compression journal January 2017

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