Sparse approximate inverse smoothers for geometric and algebraic multigrid
Applied Numerical Mathematics - Developments and trends in iterative methods for large systems of equations—in memoriam Rüdiger Weiss
BoomerAMG: a parallel algebraic multigrid solver and preconditioner
Applied Numerical Mathematics - Developments and trends in iterative methods for large systems of equations—in memoriam Rüdiger Weiss
Preconditioning techniques for large linear systems: a survey
Journal of Computational Physics
Variations on algebraic recursive multilevel solvers (ARMS) for the solution of CFD problems
Applied Numerical Mathematics
An Introduction to Algebraic Multigrid
Computing in Science and Engineering
Compatible coarsening in the multigraph algorithm
Advances in Engineering Software
Precursor simulations in spreading using a multi-mesh adaptive finite element method
Journal of Computational Physics
Journal of Scientific Computing
Estimating the Laplace-Beltrami operator by restricting 3D functions
SGP '09 Proceedings of the Symposium on Geometry Processing
Convergence analysis of multigrid methods with residual scaling techniques
Journal of Computational and Applied Mathematics
Smoothed Aggregation Multigrid for Markov Chains
SIAM Journal on Scientific Computing
SIAM Journal on Scientific Computing
On-the-Fly Adaptive Smoothed Aggregation Multigrid for Markov Chains
SIAM Journal on Scientific Computing
Journal of Computational and Applied Mathematics
On the utilization of edge matrices in algebraic multigrid
LSSC'05 Proceedings of the 5th international conference on Large-Scale Scientific Computing
Proceedings of the 2012 Symposium on High Performance Computing
A hybrid multigrid method for convection-diffusion problems
Journal of Computational and Applied Mathematics
Hi-index | 0.01 |
Algebraic multigrid (AMG) is currently undergoing a resurgence in popularity, due in part to the dramatic increase in the need to solve physical problems posed on very large, unstructured grids. While AMG has proved its usefulness on various problem types, it is not commonly understood how wide a range of applicability the method has. In this study, we demonstrate that range of applicability, while describing some of the recent advances in AMG technology. Moreover, in light of the imperatives of modern computer environments, we also examine AMG in terms of algorithmic scalability. Finally, we show some of the situations in which standard AMG does not work well and indicate the current directions taken by AMG researchers to alleviate these difficulties.