Name
Abstract | ||
|---|---|---|
Bootstrap algebraic multigrid (BAMG) is a multigrid-based solver for matrix equations of the form Ax=b. Its aim is to automatically determine the interpolation weights used in algebraic multigrid by locally fitting a set of test vectors that have been relaxed as solutions to the corresponding homogeneous equation, Ax=0. This paper studies an improved form of BAMG, called relaxation-corrected bootstrap algebraic multigrid (rBAMG), that involves adding scaled residuals of the test vectors to the least-squares equations. The basic rBAMG scheme was introduced in an earlier paper [1] and analyzed on a simplemodel problem. The purpose of the current paper is to further develop this algorithm by incorporating several new critical components and to systematically study its performance on an interesting model problem from quantum chromodynamics. Whereas the earlier paper introduced a new least-squares principle involving the residuals of the test vectors, a simple extrapolation scheme is developed here to accurately estimate the convergence factors of the evolving algebraic multigrid solver. Such a capability is essential to the effective development of a fast solver, and the approach introduced here is shown numerically to be much more effective than the conventional approach of just observing successive error reduction factors. Another component of the setup process developed here is an adaptive cycling process. This component assesses the effectiveness of the V-cycle constructed in the initial rBAMG phase by applying it to the homogeneous equation. When poor convergence is observed, the set of test vectors is enhanced with the resulting error, enabling the subsequent least-squares fit of interpolation to produce an improved V-cycle. A related component is the scaling and recombination Ritz process that targets the so- called weak approximation property in an attempt to reveal the important elements of these evolving error and test vector spaces. The aim of the numerical study documented here is to provide insight into the various design choices that arise in the development of an rBAMG algorithm. With this in mind, the results for quantum chromodynamics focus on the behavior of rBAMG in terms of the number of initial test vectors used, the number of relaxation sweeps applied to them, and the size of the target matrices. Copyright (C) 2012 John Wiley & Sons, Ltd. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1002/nla.1821 | NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS |
Keywords | Field | DocType |
iterative methods,multigrid,algebraic multigrid,adaptive algebraic multigrid | Convergence (routing),Mathematical optimization,Iterative method,Matrix (mathematics),Interpolation,Algorithm,Extrapolation,Solver,Homogeneous differential equation,Mathematics,Multigrid method | Journal |
Volume | Issue | ISSN |
19 | SP2 | 1070-5325 |
Citations | PageRank | References |
1 | 0.35 | 5 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marian Brezina | 1 | 299 | 43.34 |
| Christian Ketelsen | 2 | 1 | 0.35 |
| Thomas A. Manteuffel | 3 | 349 | 53.64 |
| STEPHEN F. MCCORMICK | 4 | 258 | 30.70 |
| Minho Park | 5 | 1 | 0.35 |
| J. Ruge | 6 | 293 | 33.76 |