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

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    Type
    Article
    Authors
    Zampini, Stefano cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Extreme Computing Research Center
    Date
    2016-10-27
    Online Publication Date
    2016-10-27
    Print Publication Date
    2016-01
    Permanent link to this record
    http://hdl.handle.net/10754/621844
    
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    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.
    Sponsors
    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
    ae974a485f413a2113503eed53cd6c53
    10.1137/15M1025785
    Scopus Count
    Collections
    Articles; Extreme Computing Research Center; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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