A general software package has been developed for solving systems of partial differential equations with adaptive multigrid methods (MLAT) on distributed memory computers. The package supports the dynamic mapping of refinement levels. The general strategy is described and results are reported on compute-intensive problems as well as on some simple problems representing worst-case situations from a parallel efficiency point of view. Inherent limitations of the parallel efficiency will be discussed. (orig.)SIGLEAvailable from TIB Hannover: RN 9844(781) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman
Abstract. We present two parallel multilevel methods for solving large-scale discretized partial dif...
266 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002.A parallel multigrid algorith...
In modern large-scale supercomputing applications, Algebraic Multigrid (AMG) is a leading choice for...
INTRODUCTION We consider partial differential equations, e.g. an elliptic scalar differential equat...
A number of experimental implementations of the multigrid algorithm for the solution of systems of p...
The multigrid algorithm is a fast and efficient (in fact provably optimal) method for solving a wide...
Numerical weather forecasting and climate predictions require enormous computing power since high re...
Abstract: Making multigrid algorithms run efficiently on large parallel computers is a challenge. Wi...
Parallel adaptive multigrid methods offer a threefold potential of accelerating structural analysis ...
A parallel multigrid method for the resolution of elliptic partial differential equations has been i...
The algebraic multigrid (AMG) approach provides a purely algebraic means to tackle the efficient sol...
. This paper presents a new approach to parallel programming with algorithmic skeletons, i.e. common...
This paper presents the design, development and application of a computational infrastructure to sup...
Domain decomposition methods are a valuable approach when solving partial differential equation (PDE...
In this article, we review the development of multigrid methods for partial differential equations o...
Abstract. We present two parallel multilevel methods for solving large-scale discretized partial dif...
266 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002.A parallel multigrid algorith...
In modern large-scale supercomputing applications, Algebraic Multigrid (AMG) is a leading choice for...
INTRODUCTION We consider partial differential equations, e.g. an elliptic scalar differential equat...
A number of experimental implementations of the multigrid algorithm for the solution of systems of p...
The multigrid algorithm is a fast and efficient (in fact provably optimal) method for solving a wide...
Numerical weather forecasting and climate predictions require enormous computing power since high re...
Abstract: Making multigrid algorithms run efficiently on large parallel computers is a challenge. Wi...
Parallel adaptive multigrid methods offer a threefold potential of accelerating structural analysis ...
A parallel multigrid method for the resolution of elliptic partial differential equations has been i...
The algebraic multigrid (AMG) approach provides a purely algebraic means to tackle the efficient sol...
. This paper presents a new approach to parallel programming with algorithmic skeletons, i.e. common...
This paper presents the design, development and application of a computational infrastructure to sup...
Domain decomposition methods are a valuable approach when solving partial differential equation (PDE...
In this article, we review the development of multigrid methods for partial differential equations o...
Abstract. We present two parallel multilevel methods for solving large-scale discretized partial dif...
266 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2002.A parallel multigrid algorith...
In modern large-scale supercomputing applications, Algebraic Multigrid (AMG) is a leading choice for...