TY - JOUR
T1 - KSPHPDDM and PCHPDDM: Extending PETSc with advanced Krylov methods and robust multilevel overlapping Schwarz preconditioners
AU - Jolivet, Pierre
AU - Roman, Jose E.
AU - Zampini, Stefano
N1 - KAUST Repository Item: Exported on 2021-02-21
Acknowledgements: The authors would like to thank S. Balay, J. Brown, V. Hapla, M. Knepley, and B. Smith for reviewing the successive merge requests in PETSc repository and for their feedback on this manuscript. This work was granted access to the GENCI-sponsored HPC resources of:, • TGCC@CEA under allocation A0070607519;, • IDRIS@CNRS under allocation AP010611780. Jose E. Roman was supported by the Spanish Agencia Estatal de Investigación (AEI) under project SLEPc-DA (PID2019-107379RB-I00).
PY - 2021/1/22
Y1 - 2021/1/22
N2 - Contemporary applications in computational science and engineering often require the solution of linear systems which may be of different sizes, shapes, and structures. The goal of this paper is to explain how two libraries, PETSc and HPDDM, have been interfaced in order to offer end-users robust overlapping Schwarz preconditioners and advanced Krylov methods featuring recycling and the ability to deal with multiple right-hand sides. The flexibility of the implementation is showcased and explained with minimalist, easy-to-run, and reproducible examples, to ease the integration of these algorithms into more advanced frameworks. The examples provided cover applications from eigenanalysis, elasticity, combustion, and electromagnetism.
AB - Contemporary applications in computational science and engineering often require the solution of linear systems which may be of different sizes, shapes, and structures. The goal of this paper is to explain how two libraries, PETSc and HPDDM, have been interfaced in order to offer end-users robust overlapping Schwarz preconditioners and advanced Krylov methods featuring recycling and the ability to deal with multiple right-hand sides. The flexibility of the implementation is showcased and explained with minimalist, easy-to-run, and reproducible examples, to ease the integration of these algorithms into more advanced frameworks. The examples provided cover applications from eigenanalysis, elasticity, combustion, and electromagnetism.
UR - http://hdl.handle.net/10754/667072
UR - https://linkinghub.elsevier.com/retrieve/pii/S0898122121000055
UR - http://www.scopus.com/inward/record.url?scp=85099617492&partnerID=8YFLogxK
U2 - 10.1016/j.camwa.2021.01.003
DO - 10.1016/j.camwa.2021.01.003
M3 - Article
SN - 0898-1221
VL - 84
SP - 277
EP - 295
JO - Computers and Mathematics with Applications
JF - Computers and Mathematics with Applications
ER -