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- Marian Brezina, Andrew J. Cleary, +5 authors John W. Ruge
- SIAM J. Scientific Computing
- 2001

We introduce AMGe, an algebraic multigrid method for solving the discrete equations that arise in Ritz-type finite element methods for partial differential equations. Assuming access to the element stiffness matrices, AMGe is based on the use of two local measures, which are derived from global measures that appear in existing multigrid theory. These new… (More)

- Marian Brezina, Robert D. Falgout, Scott P. MacLachlan, Thomas A. Manteuffel, Stephen F. McCormick, John W. Ruge
- SIAM J. Scientific Computing
- 2004

Substantial effort has been focused over the last two decades on developing multilevel iterative methods capable of solving the large linear systems encountered in engineering practice. These systems often arise from discretizing partial differential equations over unstructured meshes, and the particular parameters or geometry of the physical problem being… (More)

- Tim Chartier, Robert D. Falgout, +5 authors Panayot S. Vassilevski
- SIAM J. Scientific Computing
- 2003

Spectral AMGe (ρAMGe), is a new algebraic multigrid method for solving discretizations that arise in Ritz-type finite element methods for partial differential equations. The method assumes access to the element stiffness matrices in order to lessen certain presumptions that can limit other algebraic methods. ρAMGe uses the spectral decomposition of small… (More)

- Hans De Sterck, Thomas A. Manteuffel, Stephen F. McCormick, Quoc Nguyen, John W. Ruge
- SIAM J. Scientific Computing
- 2008

A multilevel adaptive aggregation method for calculating the stationary probability vector of an irreducible stochastic matrix is described. The method is a special case of the adaptive smooth aggregation and adaptive algebraic multigrid methods for sparse linear systems, and is also closely related to certain extensively studied iterative… (More)

- Hans De Sterck, Thomas A. Manteuffel, +4 authors Geoffrey Sanders
- SIAM J. Scientific Computing
- 2010

A smoothed aggregation multigrid method is presented for the numerical calculation of the stationary probability vector of an irreducible sparse Markov chain. It is shown how smoothing the interpolation and restriction operators can dramatically increase the efficiency of aggregation multigrid methods for Markov chains that have been proposed in the… (More)

- M Brezina, T Manteuffel, S Mccormick, J Ruge, G Sanders
- 2008

Applying smoothed aggregation multigrid (SA) to solve a nonsymmetric linear system, Ax = b, is often impeded by the lack of a minimization principle that can be used as a basis for the coarse-grid correction process. This paper proposes a Petrov-Galerkin (PG) approach based on applying SA to either of two symmetric positive definite (SPD) matrices, √ AtA or… (More)

This paper develops a least-squares approach to the solution of the incompressible Navier–Stokes equations in primitive variables. As with our earlier work on Stokes equations, we recast the Navier–Stokes equations as a first-order system by introducing a velocity-flux variable and associated curl and trace equations. We show that a least-squares principle… (More)

- Multigrid, M. Brezina, +4 authors J. Ruge
- 2005

Substantial effort has been focused over the last two decades on developing multilevel iterative methods capable of solving the large linear systems encountered in engineering practice. These systems often arise from discretizing partial differential equations over unstructured meshes, and the particular parameters or geometry of the physical problem being… (More)

- Andrew J. Cleary, Robert D. Falgout, +5 authors John W. Ruge
- SIAM J. Scientific Computing
- 2000

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… (More)

We establish an a-posteriori error estimate, with corresponding bounds, that is valid for any FOSLS L-minimization problem. Such estimates follow almost immediately from the FOSLS formulation, but they are usually difficult to establish for other methodologies. We present some numerical examples to support our theoretical results. We also establish a local… (More)