Trilinos

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 254 articles )

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  1. Alleman, Coleman N.; Foulk, James W. III; Mota, Alejandro; Lim, Hojun; Littlewood, David J.: Concurrent multiscale modeling of microstructural effects on localization behavior in finite deformation solid mechanics (2018)
  2. Badia, Santiago; Martín, Alberto F.; Principe, Javier: FEMPAR: an object-oriented parallel finite element framework (2018)
  3. Brauss, K. D.; Meir, A. J.: On a parallel, 3-dimensional, finite element solver for viscous, resistive, stationary magnetohydrodynamics equations: velocity-current formulation (2018)
  4. Constantinescu, Emil M.: Generalizing global error estimation for ordinary differential equations by using coupled time-stepping methods (2018)
  5. D’Elia, M.; Edwards, H. C.; Hu, J.; Phipps, E.; Rajamanickam, S.: Ensemble grouping strategies for embedded stochastic collocation methods applied to anisotropic diffusion problems (2018)
  6. Domino, Stefan P.: Design-order, non-conformal low-Mach fluid algorithms using a hybrid CVFEM/DG approach (2018)
  7. Elafrou, Athena; Karakasis, Vasileios; Gkountouvas, Theodoros; Kourtis, Kornilios; Goumas, Georgios; Koziris, Nectarios: SparseX: A library for high-performance sparse matrix-vector multiplication on multicore platforms (2018)
  8. Esmaily, M.; Jofre, L.; Mani, A.; Iaccarino, G.: A scalable geometric multigrid solver for nonsymmetric elliptic systems with application to variable-density flows (2018)
  9. Ke, G.; Aulisa, E.; Dillon, G.; Howle, V.: Augmented Lagrangian-based preconditioners for steady buoyancy driven flow (2018)
  10. Kramer, Richard M. J.; Siefert, Christopher M.; Voth, Thomas E.; Bochev, Pavel B.: Formulation and computation of dynamic, interface-compatible Whitney complexes in three dimensions (2018)
  11. Lin, P. T.; Shadid, J. N.; Hu, J. J.; Pawlowski, R. P.; Cyr, E. C.: Performance of fully-coupled algebraic multigrid preconditioners for large-scale VMS resistive MHD (2018)
  12. P. Cardiff, A. Karač, P. De Jaeger, H. Jasak, J. Nagy, A. Ivanković, Ž. Tuković: An open-source finite volume toolbox for solid mechanics and fluid-solid interaction simulations (2018) arXiv
  13. Phillips, Edward G.; Shadid, John N.; Cyr, Eric C.: Scalable preconditioners for structure preserving discretizations of Maxwell equations in first order form (2018)
  14. Tantet, Alexis; Lucarini, Valerio; Dijkstra, Henk A.: Resonances in a chaotic attractor crisis of the Lorenz flow (2018)
  15. Trask, Nathaniel; Maxey, Martin; Hu, Xiaozhe: A compatible high-order meshless method for the Stokes equations with applications to suspension flows (2018)
  16. Arndt, Daniel; Bangerth, Wolfgang; Davydov, Denis; Heister, Timo; Heltai, Luca; Kronbichler, Martin; Maier, Matthias; Pelteret, Jean-Paul; Turcksin, Bruno; Wells, David: The deal.II library, version 8.5 (2017)
  17. Axelsson, Owe; Farouq, Shiraz; Neytcheva, Maya: A preconditioner for optimal control problems, constrained by Stokes equation with a time-harmonic control (2017)
  18. Axelsson, Owe; Farouq, Shiraz; Neytcheva, Maya: Comparison of preconditioned Krylov subspace iteration methods for PDE-constrained optimization problems. Stokes control (2017)
  19. Baiges, Joan; Bayona, Camilo: RefficientLib: an efficient load-rebalanced adaptive mesh refinement algorithm for high-performance computational physics meshes (2017)
  20. Barone, Alessandro; Fenton, Flavio; Veneziani, Alessandro: Numerical sensitivity analysis of a variational data assimilation procedure for cardiac conductivities (2017)

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