A Comparison of Preconditioned Nonsymmetric
Krylov Methods on a Large-Scale MIMD Machine
John N. Shadid, Ray S. Tuminaro
Sandia National Laboratories
Albuquerque, New Mexico 87185
Many complex physical processes are modeled by coupled systems of
partial differential equations (PDEs). Often, the numerical
approximation of these PDEs requires the solution of large sparse nonsymmetric
systems of equations.
In this paper we compare the parallel performance of a number of
preconditioned Krylov subspace methods on a large-scale MIMD machine.
These methods are among the most robust and
efficient iterative algorithms for the solution of large sparse linear systems.
In this comparison we focus on parallel issues associated with
within the GMRES, CGS, BiCGSTAB, and QMRCGS methods.
Conclusions are drawn on the effectiveness of the different schemes
based on results obtained from a 1024 processor nCUBE 2 hypercube.