Each Trilinos package is a self-contained, independent piece of software with its own set of requirements, its own development team and group of users. Because of this, Trilinos itself is designed to respect the autonomy of packages. Trilinos offers a variety of ways for a particular package to interact with other Trilinos packages. It also offers a set of tools that can assist package developers with builds across multiple platforms, generating documentation and regression testing across a set of target platforms. At the same time, what a package must do to be called a Trilinos package is minimal, and varies with each package.

References in zbMATH (referenced in 313 articles )

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  1. de Souza Lourenço, Marcos Antonio; Martínez Padilla, Elie Luis: An octree structured finite volume based solver (2020)
  2. Grave, M.; Camata, José J.; Coutinho, Alvaro L. G. A.: Residual-based variational multiscale 2D simulation of sediment transport with morphological changes (2020)
  3. Reguly, István Z.; Mudalige, Gihan R.: Productivity, performance, and portability for computational fluid dynamics applications (2020)
  4. Abduljabbar, Mustafa; Farhan, Mohammed Al; Al-Harthi, Noha; Chen, Rui; Yokota, Rio; Bagci, Hakan; Keyes, David: Extreme scale FMM-accelerated boundary integral equation solver for wave scattering (2019)
  5. Bassett, Brody; Kiedrowski, Brian: Meshless local Petrov-Galerkin solution of the neutron transport equation with streamline-upwind Petrov-Galerkin stabilization (2019)
  6. Boggs, Paul T.; Byrd, Richard H.: Adaptive, limited-memory BFGS algorithms for unconstrained optimization (2019)
  7. Charnyi, Sergey; Heister, Timo; Olshanskii, Maxim A.; Rebholz, Leo G.: Efficient discretizations for the EMAC formulation of the incompressible Navier-Stokes equations (2019)
  8. Dissanayake, Chandani; Juan, Lourdes; Long, Kevin R.; Peace, Angela; Rana, Md Masud: Genotypic selection in spatially heterogeneous producer-grazer systems subject to stoichiometric constraints (2019)
  9. Dohrmann, Clark R.; Pierson, Kendall H.; Widlund, Olof B.: Vertex-based preconditioners for the coarse problems of BDDC (2019)
  10. Gesenhues, Linda; Camata, José J.; Côrtes, Adriano M. A.; Rochinha, Fernando A.; Coutinho, Alvaro L. G. A.: Finite element simulation of complex dense granular flows using a well-posed regularization of the (\mu(I))-rheology (2019)
  11. Heinlein, Alexander; Hochmuth, Christian; Klawonn, Axel: Monolithic overlapping Schwarz domain decomposition methods with GDSW coarse spaces for incompressible fluid flow problems (2019)
  12. Heinlein, Alexander; Klawonn, Axel; Knepper, Jascha; Rheinbach, Oliver: Adaptive GDSW coarse spaces for overlapping Schwarz methods in three dimensions (2019)
  13. Heinlein, Alexander; Klawonn, Axel; Rheinbach, Oliver; Röver, Friederike: A three-level extension of the GDSW overlapping Schwarz preconditioner in two dimensions (2019)
  14. Jiang, J.; Garikipati, K.; Rudraraju, S.: A diffuse interface framework for modeling the evolution of multi-cell aggregates as a soft packing problem driven by the growth and division of cells (2019)
  15. Kopaničáková, Alena; Krause, Rolf; Tamstorf, Rasmus: Subdivision-based nonlinear multiscale cloth simulation (2019)
  16. Kucala, Alec; Rao, Rekha; Erickson, Lindsay: A computational model for molten corium spreading and solidification (2019)
  17. Mantzaflaris, Angelos; Scholz, Felix; Toulopoulos, Ioannis: Low-rank space-time decoupled isogeometric analysis for parabolic problems with varying coefficients (2019)
  18. Roberts, Nathan V.: Camellia: a rapid development framework for finite element solvers (2019)
  19. Seo, Jongmin; Schiavazzi, Daniele E.; Marsden, Alison L.: Performance of preconditioned iterative linear solvers for cardiovascular simulations in rigid and deformable vessels (2019)
  20. Shaydulin, Ruslan; Chen, Jie; Safro, Ilya: Relaxation-based coarsening for multilevel hypergraph partitioning (2019)

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