Firedrake

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 56 articles , 1 standard article )

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  1. Sebastian Blauth: cashocs: A Computational, Adjoint-Based Shape Optimization and Optimal Control Software (2021) not zbMATH
  2. 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)
  3. Alberto Paganini, Florian Wechsung: Fireshape: a shape optimization toolbox for Firedrake (2020) arXiv
  4. Bihlo, Alex; Jackaman, James; Valiquette, Francis: On the development of symmetry-preserving finite element schemes for ordinary differential equations (2020)
  5. Farrell, Patrick E.; Gazca-Orozco, P. A.; Süli, Endre: Numerical analysis of unsteady implicitly constituted incompressible fluids: 3-field formulation (2020)
  6. He, Yunhui; MacLachlan, Scott: Two-level Fourier analysis of multigrid for higher-order finite-element discretizations of the Laplacian. (2020)
  7. Kirby, Robert C.; Coogan, Peter: Optimal-order preconditioners for the Morse-Ingard equations (2020)
  8. Matteo Giacomini, Ruben Sevilla, Antonio Huerta: HDGlab: An open-source implementation of the hybridisable discontinuous Galerkin method in MATLAB (2020) arXiv
  9. Reguly, István Z.; Mudalige, Gihan R.: Productivity, performance, and portability for computational fluid dynamics applications (2020)
  10. 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)
  11. Tom Gustafsson; G. D. McBain: scikit-fem: A Python package for finite element assembly (2020) not zbMATH
  12. Cimrman, Robert; Lukeš, Vladimír; Rohan, Eduard: Multiscale finite element calculations in Python using sfepy (2019)
  13. Cotter, Colin; Crisan, Dan; Holm, Darryl D.; Pan, Wei; Shevchenko, Igor: Numerically modeling stochastic Lie transport in fluid dynamics (2019)
  14. Farrell, Patrick E.; Mitchell, Lawrence; Wechsung, Florian: An augmented Lagrangian preconditioner for the 3D stationary incompressible Navier-Stokes equations at High Reynolds number (2019)
  15. Farrell, P. E.; Hake, J. E.; Funke, S. W.; Rognes, M. E.: Automated adjoints of coupled PDE-ODE systems (2019)
  16. Gibson, Thomas H.; McRae, Andrew T. T.; Cotter, Colin J.; Mitchell, Lawrence; Ham, David A.: Compatible finite element methods for geophysical flows. Automation and implementation using Firedrake (2019)
  17. Gillette, Andrew; Kloefkorn, Tyler; Sanders, Victoria: Computational serendipity and tensor product finite element differential forms (2019)
  18. Gjerde, Ingeborg G.; Kumar, Kundan; Nordbotten, Jan M.; Wohlmuth, Barbara: Splitting method for elliptic equations with line sources (2019)
  19. Gopal, Abinand; Trefethen, Lloyd N.: Solving Laplace problems with corner singularities via rational functions (2019)
  20. Jackaman, James; Papamikos, Georgios; Pryer, Tristan: The design of conservative finite element discretisations for the vectorial modified KdV equation (2019)

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