The parallel multigrid algorithm of Frederickson and McBryan (1987) is considered. This algorithm uses multiple coarse-grid problems (instead of one problem) in the hope of accelerating convergence and is found to have a close relationship to traditional multigrid methods. Specifically, the parallel coarse-grid correction operator is identical to a traditional multigrid coarse-grid correction operator, except that the mixing of high and low frequencies caused by aliasing error is removed. Appropriate relaxation operators can be chosen to take advantage of this property. Comparisons between the standard multigrid and the new method are made
We study the potential performance of multigrid algorithms running on massively parallel computers w...
Numerical solutions of partial differential equations (pde\u27s) are required in many physical probl...
Algebraic multigrid methods offer the hope that multigrid convergence can be achieved (for at least ...
To take full advantage of the parallelism in a standard multigrid algorithm requires as many process...
The convergence rate of standard multigrid algorithms degenerates on problems with stretched grids o...
The development of high performance, massively parallel computers and the increasing demands of comp...
Summary. Multigrid methods are among the fastest numerical algorithms for the solution of large spar...
Four totally parallel algorithms for the solution of a sparse linear system have common characterist...
Solving partial differential equations (PDEs) using analytical techniques is intractable for all but...
AbstractA single-level multigrid algorithm is developed in which coarse-grid correction is performed...
Multigrid convergence rates degenerate on problems with stretched grids or anisotropic operators, un...
This paper surveys the techniques that are necessary for constructing compu-tationally ecient parall...
A semicoarsening multigrid algorithm suitable for use on single instruction multiple data (SIMD) arc...
The need to solve linear systems arising from problems posed on extremely large, unstructured grids ...
Multigrid methods are often the most efficient approaches for solving the very large linear systems...
We study the potential performance of multigrid algorithms running on massively parallel computers w...
Numerical solutions of partial differential equations (pde\u27s) are required in many physical probl...
Algebraic multigrid methods offer the hope that multigrid convergence can be achieved (for at least ...
To take full advantage of the parallelism in a standard multigrid algorithm requires as many process...
The convergence rate of standard multigrid algorithms degenerates on problems with stretched grids o...
The development of high performance, massively parallel computers and the increasing demands of comp...
Summary. Multigrid methods are among the fastest numerical algorithms for the solution of large spar...
Four totally parallel algorithms for the solution of a sparse linear system have common characterist...
Solving partial differential equations (PDEs) using analytical techniques is intractable for all but...
AbstractA single-level multigrid algorithm is developed in which coarse-grid correction is performed...
Multigrid convergence rates degenerate on problems with stretched grids or anisotropic operators, un...
This paper surveys the techniques that are necessary for constructing compu-tationally ecient parall...
A semicoarsening multigrid algorithm suitable for use on single instruction multiple data (SIMD) arc...
The need to solve linear systems arising from problems posed on extremely large, unstructured grids ...
Multigrid methods are often the most efficient approaches for solving the very large linear systems...
We study the potential performance of multigrid algorithms running on massively parallel computers w...
Numerical solutions of partial differential equations (pde\u27s) are required in many physical probl...
Algebraic multigrid methods offer the hope that multigrid convergence can be achieved (for at least ...