FEMPAR

FEMPAR: An object-oriented parallel finite element framework. FEMPAR is an open source object oriented Fortran200X scientific software library for the high-performance scalable simulation of complex multiphysics problems governed by partial differential equations at large scales, by exploiting state-of-the-art supercomputing resources. It is a highly modularized, flexible, and extensible library, that provides a set of modules that can be combined to carry out the different steps of the simulation pipeline. FEMPAR includes a rich set of algorithms for the discretization step, namely (arbitrary-order) grad, div, and curl-conforming finite element methods, discontinuous Galerkin methods, B-splines, and unfitted finite element techniques on cut cells, combined with h-adaptivity. The linear solver module relies on state-of-the-art bulk-asynchronous implementations of multilevel domain decomposition solvers for the different discretization alternatives and block-preconditioning techniques for multiphysics problems. FEMPAR is a framework that provides users with out-of-the-box state-of-the-art discretization techniques and highly scalable solvers for the simulation of complex applications, hiding the dramatic complexity of the underlying algorithms. But it is also a framework for researchers that want to experience with new algorithms and solvers, by providing a highly extensible framework. In this work, the first one in a series of articles about FEMPAR, we provide a detailed introduction to the software abstractions used in the discretization module and the related geometrical module. We also provide some ingredients about the assembly of linear systems arising from finite element discretizations, but the software design of complex scalable multilevel solvers is postponed to a subsequent work.


References in zbMATH (referenced in 14 articles , 1 standard article )

Showing results 1 to 14 of 14.
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  1. Bonilla, Jesús; Badia, Santiago: Monotonicity-preserving finite element schemes with adaptive mesh refinement for hyperbolic problems (2020)
  2. Santiago Badia; Francesc Verdugo: Gridap: An extensible Finite Element toolbox in Julia (2020) not zbMATH
  3. Badia, Santiago; Martín, Alberto F.; Nguyen, Hieu: Balancing domain decomposition by constraints associated with subobjects (2019)
  4. Badia, Santiago; Martín, Alberto F.; Nguyen, Hieu: Physics-based balancing domain decomposition by constraints for multi-material problems (2019)
  5. Bonilla, Jesús; Badia, Santiago: Maximum-principle preserving space-time isogeometric analysis (2019)
  6. Brown, Jed; He, Yunhui; Maclachlan, Scott: Local Fourier analysis of balancing domain decomposition by constraints algorithms (2019)
  7. Peter Bastian, Markus Blatt, Andreas Dedner, Nils-Arne Dreier, Christian Engwer, René Fritze, Carsten Gräser, Christoph Grüninger, Dominic Kempf, Robert Klöfkorn, Mario Ohlberger, Oliver Sander: The DUNE Framework: Basic Concepts and Recent Developments (2019) arXiv
  8. Verdugo, Francesc; Martín, Alberto F.; Badia, Santiago: Distributed-memory parallelization of the aggregated unfitted finite element method (2019)
  9. Badia, Santiago; Martín, Alberto F.; Principe, Javier: \textttFEMPAR: an object-oriented parallel finite element framework (2018)
  10. Badia, Santiago; Martin, Alberto F.; Verdugo, Francesc: Mixed aggregated finite element methods for the unfitted discretization of the Stokes problem (2018)
  11. Badia, Santiago; Verdugo, Francesc: Robust and scalable domain decomposition solvers for unfitted finite element methods (2018)
  12. Badia, Santiago; Verdugo, Francesc; Martín, Alberto F.: The aggregated unfitted finite element method for elliptic problems (2018)
  13. Colomés, Oriol; Scovazzi, Guglielmo; Guilleminot, Johann: On the robustness of variational multiscale error estimators for the forward propagation of uncertainty (2018)
  14. Santiago Badia, Alberto F. Martin, Javier Principe: FEMPAR: An object-oriented parallel finite element framework (2017) arXiv