Overlapping Domain Decomposition Methods with FreeFem++
- 2 Citations
- 1.1k Downloads
Abstract
In this note, the performances of a framework for two-level overlapping domain decomposition methods are assessed. Numerical experiments are run on Curie, a Tier-0 system for PRACE, for two second order elliptic PDE with highly heterogeneous coefficients: a scalar equation of diffusivity and the system of linear elasticity. Those experiments yield systems with up to ten billion unknowns in 2D and one billion unknowns in 3D, solved on few thousands cores.
Keywords
Domain Decomposition Method Finite Element Space Master Process Krylov Method Local PartitionNotes
Acknowledgements
This work has been supported in part by ANR through COSINUS program (project PETALh no. ANR-10-COSI-0013 and projet HAMM no. ANR-10-COSI-0009). It was granted access to the HPC resources of TGCC@CEA made available within the Distributed European Computing Initiative by the PRACE-2IP, receiving funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement RI-283493.
References
- 1.Amestoy, P., Duff, I., L’Excellent, J.Y., Koster, J.: A fully asynchronous multifrontal solver using distributed dynamic scheduling. SIAM J. Matrix Anal. Appl. 23(1), 15–41 (2001)CrossRefzbMATHMathSciNetGoogle Scholar
- 2.Amestoy, P., Guermouche, A., L’Excellent, J.Y., Pralet, S.: Hybrid scheduling for the parallel solution of linear systems. Parallel Comput. 32(2), 136–156 (2006)CrossRefMathSciNetGoogle Scholar
- 3.Bangerth, W., Hartmann, R., Kanschat, G.: deal.II—a general-purpose object-oriented finite element library. ACM Trans. Math. Softw. 33(4), 24–27 (2007)Google Scholar
- 4.Cai, X.C., Sarkis, M.: Restricted additive Schwarz preconditioner for general sparse linear systems. SIAM J. Sci. Comput. 21(2), 792–797 (1999)CrossRefzbMATHMathSciNetGoogle Scholar
- 5.Chevalier, C., Pellegrini, F.: PT-Scotch: a tool for efficient parallel graph ordering. Parallel Comput. 34(6), 318–331 (2008)CrossRefMathSciNetGoogle Scholar
- 6.Geuzaine, C., Remacle, J.F.: Gmsh: a 3-d finite element mesh generator with built-in pre- and post-processing facilities. Int. J. Numer. Methods Eng. 79(11), 1309–1331 (2009)CrossRefzbMATHMathSciNetGoogle Scholar
- 7.Hénon, P., Ramet, P., Roman, J.: PaStiX: a high performance parallel direct solver for sparse symmetric positive definite systems. Parallel Comput. 28(2), 301–321 (2002)CrossRefzbMATHMathSciNetGoogle Scholar
- 8.Hernandez, V., Roman, J., Vidal, V.: SLEPc: a scalable and flexible toolkit for the solution of eigenvalue problems. ACM Trans. Math. Softw. 31(3), 351–362 (2005)CrossRefzbMATHMathSciNetGoogle Scholar
- 9.Jolivet, P., Dolean, V., Hecht, F., Nataf, F., Prud’homme, C., Spillane, N.: High performance domain decomposition methods on massively parallel architectures with FreeFem++. J. Numer. Math. 20(4), 287–302 (2012)zbMATHMathSciNetGoogle Scholar
- 10.Karypis, G., Kumar, V.: A fast and high quality multilevel scheme for partitioning irregular graphs. SIAM J. Sci. Comput. 20(1), 359–392 (1998)CrossRefMathSciNetGoogle Scholar
- 11.Lehoucq, R., Sorensen, D., Yang, C.: ARPACK Users’ Guide: Solution of Large-Scale Eigenvalue Problems with Implicitly Restarted Arnoldi Methods, vol. 6. Society for Industrial and Applied Mathematics, Philadelphia (1998)CrossRefGoogle Scholar
- 12.Prud’homme, C., Chabannes, V., Doyeux, V., Ismail, M., Samake, A., Pena, G.: Feel++: a computational framework for Galerkin methods and advanced numerical methods. In: ESAIM: Proceedings, vol. 38, pp. 429–455 (2012)CrossRefMathSciNetGoogle Scholar
- 13.Schenk, O., Gärtner, K.: Solving unsymmetric sparse systems of linear equations with PARDISO. Future Gener. Comput. Syst. 20(3), 475–487 (2004)CrossRefGoogle Scholar
- 14.Spillane, N., Dolean, V., Hauret, P., Nataf, F., Pechstein, C., Scheichl, R.: A robust two-level domain decomposition preconditioner for systems of PDEs. C. R. Math. 349(23), 1255–1259 (2011)CrossRefzbMATHMathSciNetGoogle Scholar
- 15.Tang, J., Nabben, R., Vuik, C., Erlangga, Y.: Comparison of two-level preconditioners derived from deflation, domain decomposition and multigrid methods. J. Sci. Comput. 39(3), 340–370 (2009)CrossRefzbMATHMathSciNetGoogle Scholar
- 16.Toselli, A., Widlund, O.: Domain Decomposition Methods—Algorithms and Theory. Series in Computational Mathematics, vol. 34. Springer, Berlin (2005)Google Scholar