ALBERTA is an Adaptive multiLevel finite element toolbox using Bisectioning refinement and Error control by Residual Techniques for scientific Applications. ALBERTA, a sequential adaptive finite-element toolbox, is being used widely in the fields of scientific and engineering computation, especially in the numerical simulation of electromagnetics. But the nature of sequentiality has become the bottle-neck while solving large scale problems. So we develop a parallel adaptive finite-element package based on ALBERTA, using ParMETIS and PETSc. The package is able to deal with any problem that ALBERT solved. Furthermore, it is suitable for distributed memory parallel computers including PC clusters

References in zbMATH (referenced in 179 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. Bespalov, Alex; Rocchi, Leonardo; Silvester, David: T-IFISS: a toolbox for adaptive FEM computation (2021)
  3. Ebenbeck, Matthias; Garcke, Harald; Nürnberg, Robert: Cahn-Hilliard-Brinkman systems for tumour growth (2021)
  4. Funken, Stefan A.; Schmidt, Anja: A coarsening algorithm on adaptive red-green-blue refined meshes (2021)
  5. Garcke, Harald; Nürnberg, Robert: Numerical approximation of boundary value problems for curvature flow and elastic flow in Riemannian manifolds (2021)
  6. Guo, Liming; Bi, Chunjia: Adaptive finite element method for nonmonotone quasi-linear elliptic problems (2021)
  7. Kavallaris, Nikos I.; Barreira, Raquel; Madzvamuse, Anotida: Dynamics of shadow system of a singular Gierer-Meinhardt system on an evolving domain (2021)
  8. Parés, N.; Nguyen, N. C.; Díez, P.; Peraire, J.: A posteriori goal-oriented bounds for the Poisson problem using potential and equilibrated flux reconstructions: application to the hybridizable discontinuous Galerkin method (2021)
  9. Agnese, Marco; Nürnberg, Robert: Fitted front tracking methods for two-phase ncompressible Navier-Stokes flow: Eulerian and ALE finite element discretizations (2020)
  10. Barrios, Tomás P.; Cascón, J. Manuel; González, María: On an adaptive stabilized mixed finite element method for the Oseen problem with mixed boundary conditions (2020)
  11. Kahle, Christian; Lam, Kei Fong: Parameter identification via optimal control for a Cahn-Hilliard-chemotaxis system with a variable mobility (2020)
  12. Sander, Oliver: DUNE -- the distributed and unified numerics environment (2020)
  13. Dörfler, Willy; Nürnberg, Robert: Discrete gradient flows for General curvature energies (2019)
  14. Garcke, Harald; Hinze, Michael; Kahle, Christian: Optimal control of time-discrete two-phase flow driven by a diffuse-interface model (2019)
  15. Hutridurga, H.; Venkataraman, C.: Heterogeneity and strong competition in ecology (2019)
  16. Kahle, Christian; Lam, Kei Fong; Latz, Jonas; Ullmann, Elisabeth: Bayesian parameter identification in Cahn-Hilliard models for biological growth (2019)
  17. Kimura, Masato; Notsu, Hirofumi; Tanaka, Yoshimi; Yamamoto, Hiroki: The gradient flow structure of an extended Maxwell viscoelastic model and a structure-preserving finite element scheme (2019)
  18. Sváček, Petr: On implementation aspects of finite element method and its application (2019)
  19. Bänsch, E.; Karakatsani, F.; Makridakis, C. G.: A posteriori error estimates for fully discrete schemes for the time dependent Stokes problem (2018)
  20. Barrett, John W.; Garcke, Harald; Nürnberg, Robert: Gradient flow dynamics of two-phase biomembranes: sharp interface variational formulation and finite element approximation (2018)

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