hypre is a software library for the solution of large, sparse linear systems on massively parallel computers. Its emphasis is on modern powerful and scalable preconditioners. hypre provides various conceptual interfaces to enable application users to access the library in the way they naturally think about their problems. This paper presents the conceptual interfaces in hypre. An overview of the preconditioners that are available in hypre is given, including some numerical results that show the efficiency of the library

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  1. Allen, Jeffery M.; Chang, Justin; Usseglio-Viretta, Francois L. E.; Graf, Peter; Smith, Kandler: A segregated approach for modeling the electrochemistry in the 3-D microstructure of li-ion batteries and its acceleration using block preconditioners (2021)
  2. Anderson, Robert; Andrej, Julian; Barker, Andrew; Bramwell, Jamie; Camier, Jean-Sylvain; Cerveny, Jakub; Dobrev, Veselin; Dudouit, Yohann; Fisher, Aaron; Kolev, Tzanio; Pazner, Will; Stowell, Mark; Tomov, Vladimir; Akkerman, Ido; Dahm, Johann; Medina, David; Zampini, Stefano: MFEM: a modular finite element methods library (2021)
  3. Boris Krasnopolsky, Alexey Medvedev: XAMG: A library for solving linear systems with multiple right-hand side vectors (2021) not zbMATH
  4. Büsing, Henrik: Efficient solution techniques for two-phase flow in heterogeneous porous media using exact Jacobians (2021)
  5. Frigo, Matteo; Castelletto, Nicola; Ferronato, Massimiliano; White, Joshua A.: Efficient solvers for hybridized three-field mixed finite element coupled poromechanics (2021)
  6. Holter, Karl Erik; Kuchta, Miroslav; Mardal, Kent-Andre: Robust preconditioning for coupled Stokes-Darcy problems with the Darcy problem in primal form (2021)
  7. Jolivet, Pierre; Roman, Jose E.; Zampini, Stefano: KSPHPDDM and PCHPDDM: extending PETSc with advanced Krylov methods and robust multilevel overlapping Schwarz preconditioners (2021)
  8. Lee, Pilhwa: Electrodiffusion with calcium-activated potassium channels in dendritic spine (2021)
  9. Su, Guanting; Pan, Tianyu; Zheng, Mengzong; Li, Qiushi: A well-defined grid line-based immersed boundary method for efficient and accurate simulations of incompressible flow (2021)
  10. Ye, Shuai; Xu, Xinhai; An, Hengbin; Yang, Xuejun: A supplementary strategy for coarsening in algebraic multigrid (2021)
  11. Ahmed, Zaheer; Izbassarov, Daulet; Costa, Pedro; Muradoglu, Metin; Tammisola, Outi: Turbulent bubbly channel flows: effects of soluble surfactant and viscoelasticity (2020)
  12. Alberto Paganini, Florian Wechsung: Fireshape: a shape optimization toolbox for Firedrake (2020) arXiv
  13. Bui, Quan M.; Osei-Kuffuor, Daniel; Castelletto, Nicola; White, Joshua A.: A scalable multigrid reduction framework for multiphase poromechanics of heterogeneous media (2020)
  14. Çuğu, İlke; Manguoğlu, Murat: A parallel multithreaded sparse triangular linear system solver (2020)
  15. Dassi, F.; Scacchi, S.: Parallel block preconditioners for three-dimensional virtual element discretizations of saddle-point problems (2020)
  16. Deborde, Julien; Milcent, Thomas; Lubin, Pierre; Glockner, Stéphane: Numerical simulations of the interaction of solitary waves and elastic structures with a fully Eulerian method (2020)
  17. Farrell, P. E.; Gazca-Orozco, P. A.: An augmented Lagrangian preconditioner for implicitly constituted non-Newtonian incompressible flow (2020)
  18. Fernandez, Felipe; Barker, Andrew T.; Kudo, Jun; Lewicki, James P.; Swartz, Kenneth; Tortorelli, Daniel A.; Watts, Seth; White, Daniel A.; Wong, Jonathan: Simultaneous material, shape and topology optimization (2020)
  19. Gratien, Jean-Marc: A robust and scalable multi-level domain decomposition preconditioner for multi-core architecture with large number of cores (2020)
  20. Kolahdouz, Ebrahim M.; Bhalla, Amneet Pal Singh; Craven, Brent A.; Griffith, Boyce E.: An immersed interface method for discrete surfaces (2020)

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