Since the early nineties, there has been a strongly increasing demand for more efficient methods to solve large sparse, unstructured linear systems of equations. For practically relevant problem sizes, classical one-level methods had already reached their limits and new hierarchical algorithms had to be developed in order to allow an efficient solution of even larger problems. This paper gives a review of the first hierarchical and purely matrix-based approach, algebraic multigrid (AMG). AMG can directly be applied, for instance, to efficiently solve various types of elliptic partial differential equations, discretized on unstructured meshes, both in 2D and 3D. Since AMG does not make use of any geometric information, it is a \plug-in" solv...
. An algebraic multigrid algorithm for symmetric, positive definite linear systems is developed base...
Algebraic Multiscale (AMS) is a recent development for the construction of efficient linear solvers ...
Algebraic multigrid (AMG) is an iterative method that is often optimal for solving the matrix equati...
Since the early 1990s, there has been a strongly increasing demand for more efficient methods to sol...
AbstractSince the early 1990s, there has been a strongly increasing demand for more efficient method...
Since the early nineties, there has been a strongly increasing demand for more efficient methods to ...
AbstractSince the early 1990s, there has been a strongly increasing demand for more efficient method...
We investigate the use of algebraic multigrid (AMG) methods for the solution of large sparse linear ...
In this paper, we present a robust and efficient algebraic multigrid preconditioned conjugate gradie...
With the ubiquity of large-scale computing resources has come significant attention to practical det...
Abstract. Algebraic Multigrid (AMG) methods were developed originally for nu-merically solving Parti...
In modern large-scale supercomputing applications, Algebraic Multigrid (AMG) is a leading choice for...
The algebraic multigrid (AMG) approach provides a purely algebraic means to tackle the efficient sol...
The algebraic multigrid (AMG) approach provides a purely algebraic means to tackle the efficient sol...
Algebraic multigrid (AMG) solves linear systems based on multigrid principles, but in a way that onl...
. An algebraic multigrid algorithm for symmetric, positive definite linear systems is developed base...
Algebraic Multiscale (AMS) is a recent development for the construction of efficient linear solvers ...
Algebraic multigrid (AMG) is an iterative method that is often optimal for solving the matrix equati...
Since the early 1990s, there has been a strongly increasing demand for more efficient methods to sol...
AbstractSince the early 1990s, there has been a strongly increasing demand for more efficient method...
Since the early nineties, there has been a strongly increasing demand for more efficient methods to ...
AbstractSince the early 1990s, there has been a strongly increasing demand for more efficient method...
We investigate the use of algebraic multigrid (AMG) methods for the solution of large sparse linear ...
In this paper, we present a robust and efficient algebraic multigrid preconditioned conjugate gradie...
With the ubiquity of large-scale computing resources has come significant attention to practical det...
Abstract. Algebraic Multigrid (AMG) methods were developed originally for nu-merically solving Parti...
In modern large-scale supercomputing applications, Algebraic Multigrid (AMG) is a leading choice for...
The algebraic multigrid (AMG) approach provides a purely algebraic means to tackle the efficient sol...
The algebraic multigrid (AMG) approach provides a purely algebraic means to tackle the efficient sol...
Algebraic multigrid (AMG) solves linear systems based on multigrid principles, but in a way that onl...
. An algebraic multigrid algorithm for symmetric, positive definite linear systems is developed base...
Algebraic Multiscale (AMS) is a recent development for the construction of efficient linear solvers ...
Algebraic multigrid (AMG) is an iterative method that is often optimal for solving the matrix equati...