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| animation:workshops:2013:pdes [2013/06/07 14:19] – [Efficient solution of large systems of non-linear PDEs in science] sbarends | animation:workshops:2013:pdes [2013/09/20 08:26] (Version actuelle) – [Efficient solution of large systems of non-linear PDEs in science] sbarends | ||
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| ====== Efficient solution of large systems of non-linear PDEs in science ====== | ====== Efficient solution of large systems of non-linear PDEs in science ====== | ||
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| - | October 7-10, 2013 \\ | + | October 7-9, 2013 \\ |
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| - | Organizing committee: | + | Scientific committe: |
| + | Co-chair | ||
| + | * **Rolf Walder**, Centre de Recherche Astrophysique de Lyon (CRAL), ENS-Lyon, France | ||
| + | * **Eric de Sturler**, Department of Mathematics, | ||
| + | |||
| + | * **Isabelle Baraffe**, University of Exeter, GB | ||
| + | * **Maxime Viallet**, Max Planck Institute for Astrophysics, | ||
| + | * **Doris Folini**, Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland & CRAL, ENS-Lyon, France | ||
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| + | Local Organizing committee: | ||
| * **Rolf Walder**, CRAL, École normale supérieure de Lyon | * **Rolf Walder**, CRAL, École normale supérieure de Lyon | ||
| + | * **Christophe Winisdoerffer**, | ||
| + | * **Mickaël Melzani**, CRAL, École normale supérieure de Lyon | ||
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| Administrative coordination: | Administrative coordination: | ||
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| * CRAL | * CRAL | ||
| - | ===== Summary | + | ===== Objectives |
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| + | Computation and simulation are at the heart of current science. Today, 3D multi-physics, | ||
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| + | A whole class of most efficient solution technique for such systems rely on Newton-Krylov (NK) solvers, the iterative use of 2 basic algorithms: the Newton algorithm to find the roots of the non-linear equations and an iterative Krylov method to solve the resulting linear part. Convergence properties of NK methods heavily depend on a good preconditioning of the matrix defining the linear system. | ||
| - | Any kind of discretization of PDEs will result in a huge, non-linear system of equations. A whole class of most efficient solution technique for such systems rely on Newton-Krylov (NK) solvers, the iterative use of 2 basic algorithms: the Newton algorithm to find the roots of the non-linear equations and an iterative Krylov method to solve the resulting linear part. Convergence properties of NK methods heavily depend on good preconditioning. – NK methods are used by the entire research community. | + | NK methods are used by the entire research community. |
| + | ===== Note ===== | ||
| + | This workshop is part of the TOFU European Research Council Project | ||