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 38 articles , 1 standard article )

Showing results 1 to 20 of 38.
Sorted by year (citations)

1 2 next

  1. Cimrman, Robert; Lukeš, Vladimír; Rohan, Eduard: Multiscale finite element calculations in python using sfepy (2019)
  2. Cotter, Colin; Crisan, Dan; Holm, Darryl D.; Pan, Wei; Shevchenko, Igor: Numerically modeling stochastic Lie transport in fluid dynamics (2019)
  3. Farrell, Patrick E.; Mitchell, Lawrence; Wechsung, Florian: An augmented Lagrangian preconditioner for the 3D stationary incompressible Navier-Stokes equations at High Reynolds number (2019)
  4. Farrell, P. E.; Hake, J. E.; Funke, S. W.; Rognes, M. E.: Automated adjoints of coupled PDE-ODE systems (2019)
  5. 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)
  6. Gillette, Andrew; Kloefkorn, Tyler; Sanders, Victoria: Computational serendipity and tensor product finite element differential forms (2019)
  7. Gjerde, Ingeborg G.; Kumar, Kundan; Nordbotten, Jan M.; Wohlmuth, Barbara: Splitting method for elliptic equations with line sources (2019)
  8. Gopal, Abinand; Trefethen, Lloyd N.: Solving Laplace problems with corner singularities via rational functions (2019)
  9. Jackaman, James; Papamikos, Georgios; Pryer, Tristan: The design of conservative finite element discretisations for the vectorial modified KdV equation (2019)
  10. Maddison, James R.; Goldberg, Daniel N.; Goddard, Benjamin D.: Automated calculation of higher order partial differential equation constrained derivative information (2019)
  11. Ovchinnikov, George V.; Zorin, Denis; Oseledets, Ivan V.: Robust regularization of topology optimization problems with \textitaposteriori error estimators (2019)
  12. Alouges, François; Aussal, Matthieu: FEM and BEM simulations with the Gypsilab framework (2018)
  13. Bauer, W.; Cotter, C. J.: Energy-enstrophy conserving compatible finite element schemes for the rotating shallow water equations with slip boundary conditions (2018)
  14. Budd, Chris J.; McRae, Andrew T. T.; Cotter, Colin J.: The scaling and skewness of optimally transported meshes on the sphere (2018)
  15. Chang, Justin; Fabien, Maurice S.; Knepley, Matthew G.; Mills, Richard T.: Comparative study of finite element methods using the time-accuracy-size (TAS) spectrum analysis (2018)
  16. Cotter, Colin J.; Graber, P. Jameson; Kirby, Robert C.: Mixed finite elements for global tide models with nonlinear damping (2018)
  17. Homolya, Miklós; Mitchell, Lawrence; Luporini, Fabio; Ham, David A.: TSFC: a structure-preserving form compiler (2018)
  18. Iglesias, José A.; Sturm, Kevin; Wechsung, Florian: Two-dimensional shape optimization with nearly conformal transformations (2018)
  19. Kirby, Robert C.: A general approach to transforming finite elements (2018)
  20. Kirby, Robert C.; Mitchell, Lawrence: Solver composition across the PDE/linear algebra barrier (2018)

1 2 next