Abstract
We introduce a class of preconditioners for general sparse matrices based on the Birkhoff–von Neumann decomposition of doubly stochastic matrices. These preconditioners are aimed primarily at solving challenging linear systems with highly unstructured and indefinite coefficient matrices. We present some theoretical results and numerical experiments on linear systems from a variety of applications.
Funding source: National Science Foundation
Award Identifier / Grant number: DMS-1418889
Funding source: Agence Nationale de la Recherche
Award Identifier / Grant number: SOLHAR (ANR-13-MONU-0007)
Funding statement: The work of Michele Benzi was supported in part by NSF grant DMS-1418889. Bora Uçar was supported in part by French National Research Agency (ANR) project SOLHAR (ANR-13-MONU-0007).
Acknowledgements
We thank Alex Pothen for his contributions to this work. This work resulted from the collaborative environment offered by the Dagstuhl Seminar 14461 on High-Performance Graph Algorithms and Applications in Computational Science (November 9–14, 2014).
References
[1] Amestoy P. R., Duff I. S., Ruiz D. and Uçar B., A parallel matrix scaling algorithm, High Performance Computing for Computational Science – VECPAR 2008, Lecture Notes in Comput. Sci. 5336, Springer, Berlin (2008), 301–313. 10.1007/978-3-540-92859-1_27Suche in Google Scholar
[2] Anzt H., Chow E. and Dongarra J., Iterative sparse triangular solves for preconditioning, Euro-Par 2015: Parallel Processing, Lecture Notes in Comput. Sci. 9233, Springer, Berlin (2015), 650–651. 10.1007/978-3-662-48096-0_50Suche in Google Scholar
[3] Benzi M., Haws J. C. and Tuma M., Preconditioning highly indefinite and nonsymmetric matrices, SIAM J. Sci. Comput. 22 (2000), no. 4, 1333–1353. 10.1137/S1064827599361308Suche in Google Scholar
[4] Birkhoff G., Tres observaciones sobre el algebra lineal, Univ. Nac. Tucumán Rev. Ser. A 5 (1946), 147–150. Suche in Google Scholar
[5] Brualdi R. A., Notes on the Birkhoff algorithm for doubly stochastic matrices, Canad.Math. Bull. 25 (1982), no. 2, 191–199. 10.4153/CMB-1982-026-3Suche in Google Scholar
[6] Brualdi R. A. and Gibson P. M., Convex polyhedra of doubly stochastic matrices. I: Applications of the permanent function, J. Combin. Theory Ser. A 22 (1977), no. 2, 194–230. 10.1016/0097-3165(77)90051-6Suche in Google Scholar
[7] Brualdi R. A. and Ryser H. J., Combinatorial Matrix Theory, Encyclopedia Math. Appl. 39, Cambridge University Press, Cambridge, 1991. 10.1017/CBO9781107325708Suche in Google Scholar
[8] Burkard R., Dell’Amico M. and Martello S., Assignment Problems, SIAM, Philadelphia, 2009. 10.1137/1.9780898717754Suche in Google Scholar
[9] Chow E. and Patel A., Fine-grained parallel incomplete LU factorization, SIAM J. Sci. Comput. 37 (2015), no. 2, C169–C193. 10.1137/140968896Suche in Google Scholar
[10] Davis T. A. and Hu Y., The University of Florida sparse matrix collection, ACM Trans. Math. Software 38 (2011), 10.1145/2049662.2049663. 10.1145/2049662.2049663Suche in Google Scholar
[11] Dolan E. D. and Moré J. J., Benchmarking optimization software with performance profiles, Math. Program. 91 (2002), no. 2, 201–213. 10.1007/s101070100263Suche in Google Scholar
[12] Duff I. S., Erisman A. M. and Reid J. K., Direct Methods for Sparse Matrices, 2nd ed., Oxford University Press, Oxford, 2017. 10.1093/acprof:oso/9780198508380.001.0001Suche in Google Scholar
[13] Duff I. S. and Koster J., The design and use of algorithms for permuting large entries to the diagonal of sparse matrices, SIAM J. Matrix Anal. Appl. 20 (1999), no. 4, 889–901. 10.1137/S0895479897317661Suche in Google Scholar
[14] Duff I. S. and Koster J., On algorithms for permuting large entries to the diagonal of a sparse matrix, SIAM J. Matrix Anal. Appl. 22 (2001), 973–996. 10.1137/S0895479899358443Suche in Google Scholar
[15] Dufossé F. and Uçar B., Notes on Birkhoff–von Neumann decomposition of doubly stochastic matrices, Linear Algebra Appl. 497 (2016), 108–115. 10.1016/j.laa.2016.02.023Suche in Google Scholar
[16] Gabow H. N. and Tarjan R. E., Algorithms for two bottleneck optimization problems, J. Algorithms 9 (1988), no. 3, 411–417. 10.1016/0196-6774(88)90031-4Suche in Google Scholar
[17] Gantmacher F. R., The Theory of Matrices. Vol. 2, Chelsea Publishing, New York, 1959. Suche in Google Scholar
[18] Halappanavar M., Pothen A., Azad A., Manne F., Langguth J. and Khan A. M., Codesign lessons learned from implementing graph matching on multithreaded architectures, IEEE Computer 48 (2015), no. 8, 46–55. 10.1109/MC.2015.215Suche in Google Scholar
[19] Horn R. A. and Johnson C. R., Matrix Analysis, 2nd ed., Cambridge University, Cambridge, 2013. Suche in Google Scholar
[20] Knight P. A. and Ruiz D., A fast algorithm for matrix balancing, IMA J. Numer. Anal. 33 (2013), no. 3, 1029–1047. 10.1093/imanum/drs019Suche in Google Scholar
[21] Knight P. A., Ruiz D. and Uçar B., A symmetry preserving algorithm for matrix scaling, SIAM J. Matrix Anal. Appl. 35 (2014), no. 3, 931–955. 10.1137/110825753Suche in Google Scholar
[22] Manguoglu M., Koyutürk M., Sameh A. H. and Grama A., Weighted matrix ordering and parallel banded preconditioners for iterative linear system solvers, SIAM J. Sci. Comput. 32 (2010), no. 3, 1201–1216. 10.1137/080713409Suche in Google Scholar
[23] Saad Y., A flexible inner-outer preconditioned GMRES algorithm, SIAM J. Sci. Comput. 14 (1993), no. 2, 461–469. 10.1137/0914028Suche in Google Scholar
[24] Sinkhorn R. and Knopp P., Concerning nonnegative matrices and doubly stochastic matrices, Pacific J. Math. 21 (1967), 343–348. 10.2140/pjm.1967.21.343Suche in Google Scholar
[25] Varga R. S., Matrix Iterative Analysis, 2nd ed., Springer, Berlin, 2000. 10.1007/978-3-642-05156-2Suche in Google Scholar
© 2017 by De Gruyter
Artikel in diesem Heft
- Frontmatter
- On the Efficiency of a Family of Steffensen-Like Methods with Frozen Divided Differences
- Preconditioning Techniques Based on the Birkhoff–von Neumann Decomposition
- A Priori and A Posteriori Estimates of Conforming and Mixed FEM for a Kirchhoff Equation of Elliptic Type
- A Time-Stepping DPG Scheme for the Heat Equation
- Hybrid Spectral Difference Methods for an Elliptic Equation
- Simplified Iterated Lavrentiev Regularization for Nonlinear Ill-Posed Monotone Operator Equations
- Monotone Difference Schemes for Weakly Coupled Elliptic and Parabolic Systems
- An Introduction to the Analysis and Implementation of Sparse Grid Finite Element Methods
- Factorized Schemes of Second-Order Accuracy for Numerically Solving Unsteady Problems
- A Parameter Robust Finite Element Method for Fourth Order Singularly Perturbed Problems
Artikel in diesem Heft
- Frontmatter
- On the Efficiency of a Family of Steffensen-Like Methods with Frozen Divided Differences
- Preconditioning Techniques Based on the Birkhoff–von Neumann Decomposition
- A Priori and A Posteriori Estimates of Conforming and Mixed FEM for a Kirchhoff Equation of Elliptic Type
- A Time-Stepping DPG Scheme for the Heat Equation
- Hybrid Spectral Difference Methods for an Elliptic Equation
- Simplified Iterated Lavrentiev Regularization for Nonlinear Ill-Posed Monotone Operator Equations
- Monotone Difference Schemes for Weakly Coupled Elliptic and Parabolic Systems
- An Introduction to the Analysis and Implementation of Sparse Grid Finite Element Methods
- Factorized Schemes of Second-Order Accuracy for Numerically Solving Unsteady Problems
- A Parameter Robust Finite Element Method for Fourth Order Singularly Perturbed Problems