Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-24T02:09:04.814Z Has data issue: false hasContentIssue false

A Geometric Space-Time Multigrid Algorithm for the Heat Equation

Published online by Cambridge University Press:  28 May 2015

Tobias Weinzierl*
Affiliation:
Institut für Informatik, Technische Universität München, Boltzmannstr. 3, 85748 Garching, Germany
Tobias Köppl*
Affiliation:
Institut für Mathematik, Technische Universität München, Boltzmannstr. 3, 85748 Garching, Germany
*
Corresponding author.Email address:[email protected]
Corresponding author.Email address:[email protected]
Get access

Abstract

We study the time-dependent heat equation on its space-time domain that is discretised by a k-spacetree. k-spacetrees are a generalisation of the octree concept and are a discretisation paradigm yielding a multiscale representation of dynamically adaptive Cartesian grids with low memory footprint. The paper presents a full approximation storage geometric multigrid implementation for this setting that combines the smoothing properties of multigrid for the equation’s elliptic operator with a multiscale solution propagation in time. While the runtime and memory overhead for tackling the all-in-one space-time problem is bounded, the holistic approach promises to exhibit a better parallel scalability than classical time stepping, adaptive dynamic refinement in space and time fall naturally into place, as well as the treatment of periodic boundary conditions of steady cycle systems, on-time computational steering is eased as the algorithm delivers guesses for the solution’s long-term behaviour immediately, and, finally, backward problems arising from the adjoint equation benefit from the the solution being available for any point in space and time.

Type
Research Article
Copyright
Copyright © Global Science Press Limited 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1] Benioff, M. R. and Lazowska, E. D. Report to the President. Computational Science: Ensuring America’s Competitiveness. President’s Information Technology Advisory Committee, 2005.Google Scholar
[2] Borzì, A. Multigrid methods for parabolic distributed optimal control problems. J. Comput. Appl. Math. 157(2), pp. 365382, 2003.Google Scholar
[3] Brandenburg, Ch., Lindemann, F., Ulbrich, M., and Ulbrich, S. Advanced numerical methods for pde constrained optimization with application to optimal design in navier stokes flow. In Engell, S., Griewank, A., Hinze, M., Leugering, G., Rannacher, R., Schulz, V, Ulbrich, M., and Ulbrich, S., editors, Constrained Optimization and Optimal Control for Partial Differential Equations, to appear. Birkhäuser Verlag, 2010.Google Scholar
[4] Dendy, J. E. Black box multigrid. J. Comput. Phys. 48(3), pp. 366386, 1982.CrossRefGoogle Scholar
[5] Gander, M. and Vandewalle, S. On the Superlinear and Linear Convergence of the Parareal Algorithm. In Widlund, O. B. and Keyes, D. E., editors, Domain Decomposition Methods in Science and Engineering XVI, volume 55 of LNCS, pp. 291298. Springer-Verlag, Berlin Heidelberg, 2007.Google Scholar
[6] Griebel, M. Zur Lösung von Finite-Differenzen- und Finite-Element-Gleichungen mittels der Hiearchischen-Transformations-Mehrgitter-Methode, volume 342/4/90 A. SFB-Bericht, Dissertation, Technische Universität München, 1990.Google Scholar
[7] Griebel, M. Multilevelmethoden als Iterationsverfahren über Erzeugendensystemen. Teubner Skripten zur Numerik. Teubner, Habilitation, Technische Universität München, 1994.Google Scholar
[8] Griebel, M. and Oeltz, D. A Sparse Grid Space-Time Discretization Scheme for Parabolic Problems. Computing. 81(1), pp. 134, 2007.Google Scholar
[9] Hackbusch, W. Parabolic multi-grid methods. In Glowinski, R. and Lions, J. L., editors, Computing Methods in Applied Sciences and Engineering VI, pp. 189197. North-Holland, 1984.Google Scholar
[10] Horton, G. The time-parallel multigrid method. Commun. Appl. Numer. M. 8(9), pp. 585595, 1992.Google Scholar
[11] Horton, G. and Vandewalle, S. A Space-Time Multigrid Method For Parabolic PDEs. Technical report, Universität Erlangen, 1993.Google Scholar
[12] Janssen, J. and Vandewalle, S. Multigrid waveform relaxation on spatial finite element meshes: The discrete-time case. SIA M. J. Numer. Anal, 33, pp. 456474, 1993.Google Scholar
[13] McCormick, S. F. Multilevel Adaptive Methods for Partial Differential Equations. SIAM, 1989.Google Scholar
[14] Melenk, J.M. and Wohlmuth, B.I. On residual-based a posteriori error estimation in hp-fem. Adv. Comput. Math. 15, pp. 311–331, 2001.Google Scholar
[15] Mitchell, W. F. and McClain, M. A. A survey of hp-adaptive strategies for elliptic partial differential equations. In Simos, T. E., editor, Recent Advances in Computational and Applied Mathematics, pp. 227–258. Springer-Verlag, Netherlands, 2011.Google Scholar
[16] van der Ven, H. An adaptive multitime multigrid algorithm for time-periodic flow simulations. J. Comput. Phys. 227(10), pp. 5286–5303, 2008.Google Scholar
[17] Weinzierl, T. A Framework for Parallel PDE Solvers on Multiscale Adaptive Cartesian Grids. Verlag Dr. Hut, 2009.Google Scholar
[18] Weinzierl, T. and Mehl, M. Peano – A Traversal and Storage Scheme for Octree-Like Adaptive Cartesian Multiscale Grids. SIA M. J. Sci. Comput. 2010. accepted.Google Scholar
[19] Womble, D. E. A Time-Stepping Algorithm for Parallel Computers. SIA M. J. Sci. Stat. Comp. 11(5), pp. 824–837, 1990.Google Scholar