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 51 articles , 1 standard article )

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  1. Bihlo, Alex; Jackaman, James; Valiquette, Francis: On the development of symmetry-preserving finite element schemes for ordinary differential equations (2020)
  2. Farrell, Patrick E.; Gazca-Orozco, P. A.; Süli, Endre: Numerical analysis of unsteady implicitly constituted incompressible fluids: 3-field formulation (2020)
  3. Kirby, Robert C.; Coogan, Peter: Optimal-order preconditioners for the Morse-Ingard equations (2020)
  4. Matteo Giacomini, Ruben Sevilla, Antonio Huerta: HDGlab: An open-source implementation of the hybridisable discontinuous Galerkin method in MATLAB (2020) arXiv
  5. Reguly, István Z.; Mudalige, Gihan R.: Productivity, performance, and portability for computational fluid dynamics applications (2020)
  6. Tom Gustafsson; G. D. McBain: scikit-fem: A Python package for finite element assembly (2020) not zbMATH
  7. Cimrman, Robert; Lukeš, Vladimír; Rohan, Eduard: Multiscale finite element calculations in Python using sfepy (2019)
  8. Cotter, Colin; Crisan, Dan; Holm, Darryl D.; Pan, Wei; Shevchenko, Igor: Numerically modeling stochastic Lie transport in fluid dynamics (2019)
  9. Farrell, Patrick E.; Mitchell, Lawrence; Wechsung, Florian: An augmented Lagrangian preconditioner for the 3D stationary incompressible Navier-Stokes equations at High Reynolds number (2019)
  10. Farrell, P. E.; Hake, J. E.; Funke, S. W.; Rognes, M. E.: Automated adjoints of coupled PDE-ODE systems (2019)
  11. 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)
  12. Gillette, Andrew; Kloefkorn, Tyler; Sanders, Victoria: Computational serendipity and tensor product finite element differential forms (2019)
  13. Gjerde, Ingeborg G.; Kumar, Kundan; Nordbotten, Jan M.; Wohlmuth, Barbara: Splitting method for elliptic equations with line sources (2019)
  14. Gopal, Abinand; Trefethen, Lloyd N.: Solving Laplace problems with corner singularities via rational functions (2019)
  15. Jackaman, James; Papamikos, Georgios; Pryer, Tristan: The design of conservative finite element discretisations for the vectorial modified KdV equation (2019)
  16. Joshaghani, M. S.; Joodat, S. H. S.; Nakshatrala, K. B.: A stabilized mixed discontinuous Galerkin formulation for double porosity/permeability model (2019)
  17. Kamensky, David; Bazilevs, Yuri: \textsctIGAr: automating isogeometric analysis with \textscFEniCS (2019)
  18. Kirby, Robert C.; Mitchell, Lawrence: Code generation for generally mapped finite elements (2019)
  19. Luporini, Fabio; Lange, Michael; Jacobs, Christian T.; Gorman, Gerard J.; Ramanujam, J.; Kelly, Paul H. J.: Automated tiling of unstructured mesh computations with application to seismological modeling (2019)
  20. Maddison, James R.; Goldberg, Daniel N.; Goddard, Benjamin D.: Automated calculation of higher order partial differential equation constrained derivative information (2019)

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