Title | ||
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Geometric scaling: a simple and effective preconditioner for linear systems with discontinuous coefficients |
Abstract | ||
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Linear systems with large differences between coefficients ("discontinuous coefficients") arise in many cases in which partial differential equations model physical phenomena in- volving heterogeneous media. The standard approach to solving such problems is to use domain decomposition (DD) techniques, with domain boundaries conforming to the bound- aries between the different media. This approach can be difficult to implement when the geometry of the domain boundaries is complicated or the grid is unstructured. This work examines the simple preconditioning technique of scaling the equations by dividing each equation by the Lp-norm of its coefficients. This preconditioning is called geometric scal- ing (GS). Although scaling is mentioned in the literature in several places as a means of improving the convergence properties of some algorithms in some cases, there is no study on the general usefulness of this approach for discontinuous coefficients. Restarted GM- RES and Bi-CGSTAB, with and without the ILUT preconditioner, were tested on several well-known problems, on the original and on the scaled systems. It is shown that GS im- proves the convergence properties of these methods. The effect of GS on the distribution of the eigenvalues is also studied. |
Year | Venue | Keywords |
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2008 | Clinical Orthopaedics and Related Research | gmres,domain decomposition,discontinuous coefficients,linear equations,partial differential equations.,parallel processing,lp-norm,gs,. bi-cgstab,geometric scaling,partial differential equation,lp norm,eigenvalues,linear system |
Field | DocType | Volume |
Coefficient matrix,Preconditioner,Linear system,System of linear equations,Mathematical analysis,Scaling,Mathematics | Journal | abs/0812.2 |
Citations | PageRank | References |
1 | 0.40 | 3 |
Authors | ||
2 |
Name | Order | Citations | PageRank |
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Dan Gordon | 1 | 210 | 21.44 |
Rachel Gordon | 2 | 183 | 17.97 |