Abstract
We describe an interpretation of parareal as a two-level additive Schwarz preconditioner in the time domain. We show that this two-level preconditioner in time is equivalent to parareal and to multigrid reduction in time (MGRIT) with F-relaxation. We also discuss the case when additional fine or coarse propagation steps are applied in the preconditioner. This leads to procedures equivalent to MGRIT with FCF-relaxation and to MGRIT with F(CF)2-relaxation or overlapping parareal. Numerical results show that these variants have faster convergence in some cases. In addition, we also apply a Krylov subspace method, namely GMRES (generalized minimal residual), to accelerate the parareal algorithm. Better convergence is obtained, especially for the advection-reaction-diffusion equation in the case when advection and reaction coefficients are large.
Similar content being viewed by others
Availability of data and materials
Not applicable.
Code availability
Not applicable.
References
Lions, J.-L., Maday, Y., Turinici, G.: A “parareal” in time discretization of PDE’s. Comptes Rendus de l’Académie des Sci.- Series I - Math. 332, 661–668 (2001). https://doi.org/10.1016/S0764-4442(00)01793-6
Baffico, L., Bernard, S., Maday, Y., Turinici, G., Zérah, G.: Parallel-in-time molecular-dynamics simulations. Phys. Rev. E 66, 057701 (2002). https://doi.org/10.1103/PhysRevE.66.057701
Eghbal, A., Gerber, A.G., Aubanel, E.: Acceleration of unsteady hydrodynamic simulations using the parareal algorithm. J. Comput. Sci. 19, 57–76 (2016). https://doi.org/10.1016/j.jocs.2016.12.006
Baudron, A.M., Lautard, J.J., Maday, Y., Mula, O.: The parareal in time algorithm applied to the kinetic neutron diffusion equation. In: Domain decomposition methods in science and engineering XXI. Lecture notes in computational science and engineering, pp 437–445. Springer (2014). https://doi.org/10.1007/978-3-319-05789-7_41
Baudron, A.M., Lautard, J.J., Maday, Y., Riahi, M.K., Salomon, J.: Parareal in time 3D numerical solver for the LWR benchmark neutron diffusion transient model. J. Comput. Phys. 279(0), 67–79 (2014). https://doi.org/10.1016/j.jcp.2014.08.037
Kaber, S.M., Maday, Y.: Parareal in time approximation of the Korteveg-deVries-Burgers’ equations. PAMM 7, 1026403–1026404 (2007). https://doi.org/10.1002/pamm.20070057
Dai, X., Le Bris, C., Legoll, F., Maday, Y.: Symmetric parareal algorithms for Hamiltonian systems. ESAIM: Math. Model. Numerical Anal. 47, 717–742 (2013). https://doi.org/10.1051/m2an/2012046
Gander, M.J., Hairer, E.: Analysis for parareal algorithms applied to Hamiltonian differential equations. J. Comput. Appl. Math. 259 Part A(0), 2–13 (2014). Proceedings of the Sixteenth International Congress on Computational and Applied Mathematics (ICCAM-2012), Ghent, Belgium 9-13 July, 2012, https://doi.org/10.1016/j.cam.2013.01.011
Bal, G., Maday, Y.: A “parareal” time discretization for non-linear PDE’s with application to the pricing of an American put. In: Pavarino, L., Toselli, A. (eds.) Recent Developments in Domain Decomposition Methods. Lecture notes in computational science and engineering, vol. 23, pp. 189–202. Springer (2002). https://doi.org/10.1007/978-3-642-56118-4_12
Pagès, G., Pironneau, O., Sall, G.: The parareal algorithm for american options. SIAM J. Financial Math. 9(3), 966–993 (2018). https://doi.org/10.1137/17M1138832
Magoulès, F., Gbikpi-Benissan, G., Zou, Q.: Asynchronous iterations of parareal algorithm for option pricing models. Mathematics, vol. 6(4). https://doi.org/10.3390/math6040045 (2018)
Bal, G.: On the convergence and the stability of the parareal algorithm to solve partial differential equations. In: Barth, T.J., Griebel, M., Keyes, D.E., Nieminen, R.M., Roose, D., Schlick, T., Kornhuber, R., Hoppe, R., Périaux, J., Pironneau, O., Widlund, O., Xu, J. (eds.) Domain Decomposition Methods in Science and Engineering, pp. 425–432. Springer (2005)
Gander, M.J., Vandewalle, S.: Analysis of the parareal time-parallel time-integration method. SIAM J. Sci. Comput. 29(2), 556–578 (2007). https://doi.org/10.1137/05064607X
Staff, G.A., RØnquist, E.M.: Stability of the parareal algorithm. In: Barth, T.J., Griebel, M., Keyes, D.E., Nieminen, R.M., Roose, D., Schlick, T., Kornhuber, R., Hoppe, R., Périaux, J., Pironneau, O., Widlund, O., Xu, J. (eds.) Domain Decomposition Methods in Science and Engineering, pp. 449–456. Springer (2005)
Gander, M.J., Hairer, E.: Nonlinear convergence analysis for the parareal algorithm. In: Langer, U., Discacciati, M., Keyes, D.E., Widlund, O.B., Zulehner, W. (eds.) Domain Decomposition Methods in Science and Engineering XVII, pp 45–56. Springer (2008)
Minion, M.L., Williams, S.A.: Parareal and spectral deferred corrections. In: AIP conference proceedings, vol. 1048, pp. 388 (2008). https://doi.org/10.1063/1.2990941
Minion, M.L.: A hybrid parareal spectral deferred corrections method. Commun. Appl. Math. Comput. Sci. 5(2), 265–301 (2010). https://doi.org/10.2140/camcos.2010.5.265
Gander, M.J., Jiang, Y.L., Li, R.J.: Parareal Schwarz waveform relaxation methods. In: Bank, R., Holst, M., Widlund, O., Xu, J. (eds.) Domain Decomposition Methods in Science and Engineering XX. Lecture notes in computational science and engineering, vol. 91, pp. 451–458. Springer (2013). https://doi.org/10.1007/978-3-642-35275-1_53
Gander, M., Jiang, Y., Song, B.: A superlinear convergence estimate for the parareal schwarz waveform relaxation algorithm. SIAM J. Sci. Comput. 41(2), 1148–1169 (2019). https://doi.org/10.1137/18M1177226
Friedhoff, S., Falgout, R.D., Kolev, T.V., MacLachlan, S.P., Schroder, J.B.: A multigrid-in-time algorithm for solving evolution equations in parallel. In: Presented At: sixteenth copper mountain conference on multigrid methods, copper mountain, CO, United States, 17-22 Mar, 2013 (2013). http://www.osti.gov/scitech/servlets/purl/1073108
Falgout, R.D., Friedhoff, S., Kolev, T.V., MacLachlan, S.P., Schroder, J.B.: Parallel time integration with multigrid. SIAM J. Sci. Comput. 36, 635–661 (2014). https://doi.org/10.1137/130944230
Hessenthaler, A., Nordsletten, D., Rḧrle, O., Schroder, J.B., Falgout, R.D.: Convergence of the multigrid reduction in time algorithm for the linear elasticity equations. Numerical Linear Algebra Appl. 25(3), 2155 (2018). https://doi.org/10.1002/nla.2155
Chan, T.F., Mathew, T.P.: Domain decomposition algorithms. Acta. Numerica. 3, 61–143 (1994). https://doi.org/10.1017/S0962492900002427
Toselli, A., Widlund, O.: Domain Decomposition Methods – Algorithms and Theory. Springer Series in Computational Mathematics. 34 (2005). https://doi.org/10.1007/b137868
Dobrev, V., Kolev, T., Petersson, N., Schroder, J.: Two-level convergence theory for parallel time integration with multigrid. SIAM J. Scientific Comput. 39, 501–527 (2017). https://doi.org/10.1137/16M1074096
Gander, M.J., Kwok, F., Zhang, H.: Multigrid interpretations of the parareal algorithm leading to an overlapping variant and MGRIT. Comput. Visualization Sci. https://doi.org/10.1007/s00791-018-0297-y (2018)
Ruprecht, D.: Convergence of Parareal with spatial coarsening. PAMM 14(1), 1031–1034 (2014). https://doi.org/10.1002/pamm.201410490
Hirsch, C.: Numerical computation of internal and external flows: the fundamentals of computational fluid dynamics. Elsevier. https://www.bibsonomy.org/bibtex/2dbbc53f6feab1cd458e1c4f2a5c7e11c/tobydriscoll (2007)
Nevanlinna, O.: Linear acceleration of picard-lindelöf iteration. Numer. Math. 57, 147–156 (1990). https://doi.org/10.1007/BF01386404
Minion, M.: A hybrid parareal spectral deferred corrections method. Commun. Appl. Math. Comput. Sci., vol. 5. https://doi.org/10.2140/camcos.2010.5.265 (2010)
Acknowledgements
We would like to thank Martin J. Gander for his valuable discussions and the reviewers for constructive comments that helped us improve the manuscript.
Funding
Funding was provided by the French National Research Agency (ANR) Contract ANR-15-CE23-0019 (project CINE-PARA).
Author information
Authors and Affiliations
Contributions
- Describe an interpretation of parareal as a two-level additive Schwarz preconditioner in the time domain so-called SC two-level additive Schwarz in time preconditioner.
- Show the equivalence between the three methods: SC two-level additive Schwarz in time preconditioner, MGRIT with F-relaxation and parareal.
- Introduce some variants as SCS, S(CS)2 two-level additive Schwarz in time preconditioner and show their equivalence to MGRIT with FCF-relaxation, and to MGRIT with F(CF)2-relaxation or overlapping parareal.
- Propose a variant referred to as SCS2 two-level additive Schwarz in time preconditioner which converges faster and efficiently exploits parallel computing.
- Present the convergence analysis and convergence estimate of SC two-level additive Schwarz in time preconditioner and its variants.
- Present the computational cost analysis of parareal with GMRES acceleration.
- Conduct numerical experiments to show the equivalence between parareal and SC two-level additive Schwarz in time preconditioner, the comparison between SC two-level additive Schwarz in time preconditioner and its variants, the acceleration of parareal with GMRES and the computational cost comparison.
Corresponding author
Ethics declarations
Ethics approval
Not applicable.
Consent to participate
Not applicable.
Consent for publication
The authors approved it for publication.
Conflict of interest
The authors declare no competing interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Laura Grigori contributed equally to this work.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Nguyen, VT., Grigori, L. Interpretation of parareal as a two-level additive Schwarz in time preconditioner and its acceleration with GMRES. Numer Algor 94, 29–72 (2023). https://doi.org/10.1007/s11075-022-01492-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11075-022-01492-8