The efficiency and accuracy of grid-based computational fluid dynamics methods are
strongly dependent on the chosen cell size. The computational time increases exponentially …

In this paper, we examine deflation-based algebraic multigrid methods for solving large
systems of linear equations. Aggregation of the unknown terms is applied for coarsening …

During the last decades, multigrid methods have been extensively used in order to solve
large scale linear systems derived from the discretization of partial differential equations …

Since the introduction of the Algebraic MultiGrid algorithm (AMG) over twenty years ago,
significant progress has been made in improving the coarsening and the convergence …

New parallel computational techniques are introduced for the parallelization of Generic
Approximate Sparse Inverse multigrid methods, based on Portable Operating System …

In this paper we reformulate a class of non-linear variational models for global and selective
image segmentation and obtain convergent multigrid solutions. In contrast, non-linear …

During the last decades, research efforts have been focused on the derivation of effective
preconditioned iterative methods. The preconditioned iterative methods are mainly …

Through the last decades multigrid methods have been used extensively in the solution of
large sparse linear systems derived from the discretization of Partial Differential Equations in …

During the last decades, Multigrid methods have been extensively used for solving large
sparse linear systems. Considering their efficiency and the convergence behavior, Multigrid …

Purpose–The purpose of this paper is to propose multigrid methods in conjunction with
explicit approximate inverses with various cycles strategies and comparison with the other …