Add to ORKGA semicoarsening multigrid algorithm suitable for use on single instruction multiple data (SIMD) architectures has been implemented on the CM-2. The method performs well for strongly anisotropic problems and for problems with coefficients jumping by orders of magnitude across internal interfaces. The parallel efficiency of this method is analyzed, and its actual performance is compared with its performance on some other machines, both parallel and nonparallel
Numerical solutions of partial differential equations (pde\u27s) are required in many physical probl...
The development of high performance, massively parallel computers and the increasing demands of comp...
The algebraic multigrid (AMG) approach provides a purely algebraic means to tackle the efficient sol...
A semicoarsening multigrid algorithm suitable for use on single instruction multiple data (SIMD) arc...
The convergence rate of standard multigrid algorithms degenerates on problems with stretched grids o...
The parallel multigrid algorithm of Frederickson and McBryan (1987) is considered. This algorithm us...
Computational issues relevant to parallel efficiency and algorithm scalability are explored on three...
Multigrid convergence rates degenerate on problems with stretched grids or anisotropic operators, un...
Multigrid methods are studied for solving elliptic partial differential equations. Focus is on paral...
Abstract. Algebraic multigrid methods for large, sparse linear systems are a necessity in many compu...
Summary. Multigrid methods are among the fastest numerical algorithms for the solution of large spar...
Multigrid methods can be formulated as an algorithm for an abstract problem that is independent of t...
The multigrid algorithm is a fast and efficient (in fact provably optimal) method for solving a wide...
Multigrid methods are well suited to large massively parallel computer architectures because they ar...
Efficient solution of partial differential equations require a match between the algorithm and the t...
Numerical solutions of partial differential equations (pde\u27s) are required in many physical probl...
The development of high performance, massively parallel computers and the increasing demands of comp...
The algebraic multigrid (AMG) approach provides a purely algebraic means to tackle the efficient sol...
A semicoarsening multigrid algorithm suitable for use on single instruction multiple data (SIMD) arc...
The convergence rate of standard multigrid algorithms degenerates on problems with stretched grids o...
The parallel multigrid algorithm of Frederickson and McBryan (1987) is considered. This algorithm us...
Computational issues relevant to parallel efficiency and algorithm scalability are explored on three...
Multigrid convergence rates degenerate on problems with stretched grids or anisotropic operators, un...
Multigrid methods are studied for solving elliptic partial differential equations. Focus is on paral...
Abstract. Algebraic multigrid methods for large, sparse linear systems are a necessity in many compu...
Summary. Multigrid methods are among the fastest numerical algorithms for the solution of large spar...
Multigrid methods can be formulated as an algorithm for an abstract problem that is independent of t...
The multigrid algorithm is a fast and efficient (in fact provably optimal) method for solving a wide...
Multigrid methods are well suited to large massively parallel computer architectures because they ar...
Efficient solution of partial differential equations require a match between the algorithm and the t...
Numerical solutions of partial differential equations (pde\u27s) are required in many physical probl...
The development of high performance, massively parallel computers and the increasing demands of comp...
The algebraic multigrid (AMG) approach provides a purely algebraic means to tackle the efficient sol...