SIAM Journal on Scientific and Statistical Computing · 1992 · 41 citations · 9 references
ComputingComputational EngineeringComputer ScienceAlgorithmsComputational MechanicsScientific ComputingConvergence AnalysisFinite Difference MethodsIterative SolversNumerical AlgorithmsNumerical AnalysisNumerical Methods For Differential EquationsFinite Difference SchemesFinite Difference Solution Of Partial Differential EquationsGmresIterative Boundary RefinementIterative Methods For Linear SystemsIterative RefinementNewton ConvergenceNewton's Method As A Fixed Point Process
Consideration of an abstract improvement algorithm leads to the following principle, which is similar to that underlying iterative refinement: By making judicious use of relatively few high accuracy computations, high accuracy solutions can be obtained very efficiently by the algorithm. This principle is applied specifically to ${\text{GMRES}}(m)$ here; it can be similarly applied to a number of other “restarted” iterative linear methods as well. Results are given for numerical experiments in solving a discretized linear elliptic boundary value problem and in computing a step of an inexact Newton method using finite differences for a discretized nonlinear elliptic boundary value problem.
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Ron S. Dembo, Stanley C. Eisenstat, Trond Steihaug · SIAM Journal on Numerical Analysis · 1982 · 1.6K citations