An Algebraic Multigrid Preconditioner for a Class of Singular M-Matrices

Authors:
Elena Virnik
Affiliations:
-
Venue:
SIAM Journal on Scientific Computing
Year:
2007

Citing 0
Cited 6

Smoothed Aggregation Multigrid for Markov Chains

SIAM Journal on Scientific Computing
Algebraic Multigrid for Markov Chains

SIAM Journal on Scientific Computing
Top-level acceleration of adaptive algebraic multilevel methods for steady-state solution to Markov chains

Advances in Computational Mathematics
Triangular and skew-symmetric splitting method for numerical solutions of Markov chains

Computers & Mathematics with Applications
On-the-Fly Adaptive Smoothed Aggregation Multigrid for Markov Chains

SIAM Journal on Scientific Computing
A Bootstrap Algebraic Multilevel Method for Markov Chains

SIAM Journal on Scientific Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

We apply algebraic multigrid (AMG) as a preconditioner for solving large singular linear systems of the type $(I-T^T)x=0$ with GMRES. Here, $T$ is assumed to be the transition matrix of a Markov process. Although AMG and GMRES were originally designed for the solution of regular systems, with adequate adaptation their applicability can be extended to problems as described above.