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Stabilising aggregation AMG

Authors: Frank Hülsemann

Published in: Dagstuhl Seminar Proceedings, Volume 9061, Combinatorial Scientific Computing (2009)


Abstract
When applied to linear systems arising from scalar elliptic partial differential equations, algebraic multigrid (AMG) schemes based on aggregation exhibit a mesh size dependent convergence behaviour. As the number of iterations increases with the number of unknowns in the linear system, the computational complexity of such a scheme is non-optimal. This contribution presents a stabilisation of the aggregation AMG algorithm which adds a number of subspace projection steps at different stages of the algorithm and allows for variable cycling strategies. Numerical results illustrate the advantage of the stabilised algorithm over its original formulation.

Cite as

Frank Hülsemann. Stabilising aggregation AMG. In Combinatorial Scientific Computing. Dagstuhl Seminar Proceedings, Volume 9061, pp. 1-4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)


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@InProceedings{hulsemann:DagSemProc.09061.17,
  author =	{H\"{u}lsemann, Frank},
  title =	{{Stabilising aggregation AMG}},
  booktitle =	{Combinatorial Scientific Computing},
  pages =	{1--4},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9061},
  editor =	{Uwe Naumann and Olaf Schenk and Horst D. Simon and Sivan Toledo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.09061.17},
  URN =		{urn:nbn:de:0030-drops-20946},
  doi =		{10.4230/DagSemProc.09061.17},
  annote =	{Keywords: Algebraic multigrid, aggregation, stabilisation}
}
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