Firedrake is an automated system for the portable solution of partial differential equations using the finite element method (FEM). Firedrake enables users to employ a wide range of discretisations to an infinite variety of PDEs and employ either conventional CPUs or GPUs to obtain the solution. Firedrake employs the Unifed Form Language (UFL) from the FEniCS Project while the parallel execution of FEM assembly is accomplished by the PyOP2 system. The global mesh data structures, as well as linear and non-linear solvers, are provided by PETSc.

References in zbMATH (referenced in 67 articles , 1 standard article )

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  1. Bastian, Peter; Blatt, Markus; Dedner, Andreas; Dreier, Nils-Arne; Engwer, Christian; Fritze, René; Gräser, Carsten; Grüninger, Christoph; Kempf, Dominic; Klöfkorn, Robert; Ohlberger, Mario; Sander, Oliver: The \textscDuneframework: basic concepts and recent developments (2021)
  2. Kamensky, David: Open-source immersogeometric analysis of fluid-structure interaction using FEniCS and tIGAr (2021)
  3. Keilegavlen, Eirik; Berge, Runar; Fumagalli, Alessio; Starnoni, Michele; Stefansson, Ivar; Varela, Jhabriel; Berre, Inga: PorePy: an open-source software for simulation of multiphysics processes in fractured porous media (2021)
  4. Kirby, Robert C.; Kernell, Tate: Preconditioning mixed finite elements for tide models (2021)
  5. Sebastian Blauth: cashocs: A Computational, Adjoint-Based Shape Optimization and Optimal Control Software (2021) not zbMATH
  6. Zimmerman, Alexander G.; Kowalski, Julia: Mixed finite elements for convection-coupled phase-change in enthalpy form: open software verified and applied to 2D benchmarks (2021)
  7. Abhyankar, Shrirang; Betrie, Getnet; Maldonado, Daniel Adrian; Mcinnes, Lois C.; Smith, Barry; Zhang, Hong: PETSc DMNetwork: a library for scalable network PDE-based multiphysics simulations (2020)
  8. Alberto Paganini, Florian Wechsung: Fireshape: a shape optimization toolbox for Firedrake (2020) arXiv
  9. Bihlo, Alex; Jackaman, James; Valiquette, Francis: On the development of symmetry-preserving finite element schemes for ordinary differential equations (2020)
  10. Farrell, Patrick E.; Gazca-Orozco, P. A.; Süli, Endre: Numerical analysis of unsteady implicitly constituted incompressible fluids: 3-field formulation (2020)
  11. Farrell, P. E.; Gazca-Orozco, P. A.: An augmented Lagrangian preconditioner for implicitly constituted non-Newtonian incompressible flow (2020)
  12. He, Yunhui; MacLachlan, Scott: Two-level Fourier analysis of multigrid for higher-order finite-element discretizations of the Laplacian. (2020)
  13. Kirby, Robert C.; Coogan, Peter: Optimal-order preconditioners for the Morse-Ingard equations (2020)
  14. Matteo Giacomini, Ruben Sevilla, Antonio Huerta: HDGlab: An open-source implementation of the hybridisable discontinuous Galerkin method in MATLAB (2020) arXiv
  15. Reguly, István Z.; Mudalige, Gihan R.: Productivity, performance, and portability for computational fluid dynamics applications (2020)
  16. Roy, Thomas; Jönsthövel, Tom B.; Lemon, Christopher; Wathen, Andrew J.: A constrained pressure-temperature residual (CPTR) method for non-isothermal multiphase flow in porous media (2020)
  17. Tom Gustafsson; G. D. McBain: scikit-fem: A Python package for finite element assembly (2020) not zbMATH
  18. Valseth, Eirik; Romkes, Albert: Goal-oriented error estimation for the automatic variationally stable FE method for convection-dominated diffusion problems (2020)
  19. Wimmer, Golo A.; Cotter, Colin J.; Bauer, Werner: Energy conserving upwinded compatible finite element schemes for the rotating shallow water equations (2020)
  20. Bendall, Thomas M.; Cotter, Colin J.; Shipton, Jemma: The `recovered space’ advection scheme for lowest-order compatible finite element methods (2019)

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