PCBDDC: A Class of Robust Dual-Primal Methods in PETSc

Type
Article

Authors
Zampini, Stefano

KAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Extreme Computing Research Center

Online Publication Date
2016-10-27

Print Publication Date
2016-01

Date
2016-10-27

Abstract
A class of preconditioners based on balancing domain decomposition by constraints methods is introduced in the Portable, Extensible Toolkit for Scientific Computation (PETSc). The algorithm and the underlying nonoverlapping domain decomposition framework are described with a specific focus on their current implementation in the library. Available user customizations are also presented, together with an experimental interface to the finite element tearing and interconnecting dual-primal methods within PETSc. Large-scale parallel numerical results are provided for the latest version of the code, which is able to tackle symmetric positive definite problems with highly heterogeneous distributions of the coefficients. Current limitations and future extensions of the preconditioner class are also discussed.

Citation
Zampini S (2016) PCBDDC: A Class of Robust Dual-Primal Methods in PETSc. SIAM Journal on Scientific Computing 38: S282–S306. Available: http://dx.doi.org/10.1137/15M1025785.

Acknowledgements
The author wishes to thank the KAUST Supercomputing Laboratory and Cray Inc. for early access to Shaheen and the Swiss National Supercomputing Centre (CSCS), in particular its director Thomas Schultess, for access to the Cray XC40 PizDora. The author is also grateful to Prof. O. B. Widlund, Prof. D. Keyes, and two anonymous referees for valuable comments and suggestions which helped improve the manuscript.

Publisher
Society for Industrial & Applied Mathematics (SIAM)

Journal
SIAM Journal on Scientific Computing

DOI
10.1137/15M1025785

Additional Links
http://epubs.siam.org/doi/10.1137/15M1025785

Permanent link to this record