Andrew J. Cleary

ScaLAPACK users' guide

Where you can find the scalapack users guide easily? Is it in the book store? On-line book store? are you sure? Keep in mind that you will find the book in this site. This book is very referred for you because it gives not only the experience but also lesson. The lessons are very valuable to serve for you, thats not about who are reading this scalapack users guide book. It is about this book that will give wellness for all people from many societies.

Robustness and Scalability of Algebraic Multigrid

Algebraic multigrid (AMG) is currently undergoing a resurgence in popularity, due in part to the dramatic increase in the need to solve physical problems posed on very large, unstructured grids. While AMG has proved its usefulness on various problem types, it is not commonly understood how wide a range of applicability the method has. In this study, we demonstrate that range of applicability, while describing some of the recent advances in AMG technology. Moreover, in light of the imperatives of modern computer environments, we also examine AMG in terms of algorithmic scalability. Finally, we show some of the situations in which standard AMG does not work well and indicate the current directions taken by AMG researchers to alleviate these difficulties.

Coarse-Grid Selection for Parallel Algebraic Multigrid

The need to solve linear systems arising from problems posed on extremely large, unstructured grids has sparked great interest in parallelizing algebraic multigrid (AMG). To date, however, no parallel AMG algorithms exist. We introduce a parallel algorithm for the selection of coarse-grid points, a crucial component of AMG, based on modifications of certain parallel independent set algorithms and the application of heuristics designed to insure the quality of the coarse grids. A prototype serial version of the algorithm is implemented, and tests are conducted to determine its effect on multigrid convergence, and AMG complexity.

Practical Experience in the Dangers of Heterogeneous Computing

Special challenges exist in writing reliable numerical library software for heterogeneous computing environments. Although a lot of software for distributed memory parallel computers has been written, porting this software to a network of workstations requires careful consideration. The symptoms of heterogeneous computing failures can range from erroneous results without warning to deadlock. Some of the problems are straightforward to solve, but for others the solutions are not so obvious, or incur an unacceptable overhead. Making software robust on heterogeneous systems often requires additional communication.

A Comparison of Parallel Solvers for Diagonally Dominant and General Narrow-Banded Linear Systems II

We continue the comparison of parallel algorithms for solving diagonally dominant and general narrow-banded linear systems of equations that we started in [2]. The solvers compared are the banded system solvers of ScaLAPACK [6] and those investigated by Arbenz and Hegland [1, 5]. We present the numerical experiments that we conducted on the IBM SP/2.