Article ; Online: A Survey of Low-Rank Updates of Preconditioners for Sequences of Symmetric Linear Systems
Algorithms, Vol 13, Iss 100, p
2020 Volume 100
Abstract: The aim of this survey is to review some recent developments in devising efficient preconditioners for sequences of symmetric positive definite (SPD) linear systems ... ... ... ... ... A ... ... k ... ... ... < ... ...
Abstract | The aim of this survey is to review some recent developments in devising efficient preconditioners for sequences of symmetric positive definite (SPD) linear systems <math display="inline"> <semantics> <mrow> <msub> <mi>A</mi> <mi>k</mi> </msub> <msub> <mi mathvariant="bold">x</mi> <mi>k</mi> </msub> <mo>=</mo> <msub> <mi mathvariant="bold">b</mi> <mi>k</mi> </msub> <mo>,</mo> <mi>k</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mi>…</mi> </mrow> </semantics> </math> arising in many scientific applications, such as discretization of transient Partial Differential Equations (PDEs), solution of eigenvalue problems, (Inexact) Newton methods applied to nonlinear systems, rational Krylov methods for computing a function of a matrix. In this paper, we will analyze a number of techniques of updating a given initial preconditioner by a low-rank matrix with the aim of improving the clustering of eigenvalues around 1, in order to speed-up the convergence of the Preconditioned Conjugate Gradient (PCG) method. We will also review some techniques to efficiently approximate the linearly independent vectors which constitute the low-rank corrections and whose choice is crucial for the effectiveness of the approach. Numerical results on real-life applications show that the performance of a given iterative solver can be very much enhanced by the use of low-rank updates. |
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Keywords | preconditioners ; conjugate gradient method ; sparse matrices ; low-rank updates ; Industrial engineering. Management engineering ; T55.4-60.8 ; Electronic computers. Computer science ; QA75.5-76.95 |
Subject code | 518 |
Language | English |
Publishing date | 2020-04-01T00:00:00Z |
Publisher | MDPI AG |
Document type | Article ; Online |
Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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