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. 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)
  2. Büsing, Henrik: Efficient solution techniques for two-phase flow in heterogeneous porous media using exact Jacobians (2021)
  3. Jolivet, Pierre; Roman, Jose E.; Zampini, Stefano: KSPHPDDM and PCHPDDM: extending PETSc with advanced Krylov methods and robust multilevel overlapping Schwarz preconditioners (2021)
  4. Alberto Paganini, Florian Wechsung: Fireshape: a shape optimization toolbox for Firedrake (2020) arXiv
  5. Bui, Quan M.; Osei-Kuffuor, Daniel; Castelletto, Nicola; White, Joshua A.: A scalable multigrid reduction framework for multiphase poromechanics of heterogeneous media (2020)
  6. Çuğu, İlke; Manguoğlu, Murat: A parallel multithreaded sparse triangular linear system solver (2020)
  7. 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)
  8. Farrell, P. E.; Gazca-Orozco, P. A.: An augmented Lagrangian preconditioner for implicitly constituted non-Newtonian incompressible flow (2020)
  9. Gratien, Jean-Marc: A robust and scalable multi-level domain decomposition preconditioner for multi-core architecture with large number of cores (2020)
  10. Kolahdouz, Ebrahim M.; Bhalla, Amneet Pal Singh; Craven, Brent A.; Griffith, Boyce E.: An immersed interface method for discrete surfaces (2020)
  11. Kulkarni, Tejas; Buttay, Romain; Kasbaoui, M. Houssem; Attili, Antonio; Bisetti, Fabrizio: Reynolds number scaling of burning rates in spherical turbulent premixed flames (2020)
  12. Liu, Ju; Yang, Weiguang; Dong, Melody; Marsden, Alison L.: The nested block preconditioning technique for the incompressible Navier-Stokes equations with emphasis on hemodynamic simulations (2020)
  13. Pazner, Will: Efficient low-order refined preconditioners for high-order matrix-free continuous and discontinuous Galerkin methods (2020)
  14. Peng, Zhichao; Tang, Qi; Tang, Xian-Zhu: An adaptive discontinuous Petrov-Galerkin method for the Grad-Shafranov equation (2020)
  15. Reguly, István Z.; Mudalige, Gihan R.: Productivity, performance, and portability for computational fluid dynamics applications (2020)
  16. Roy, Thomas; Jönsthövel, Tom B.; Lemon, Christopher; Wathen, Andrew J.: A constrained pressure-temperature residual (CPTR) method for non-isothermal multiphase flow in porous media (2020)
  17. Sashikumaar Ganesan, Manan Shah: SParSH-AMG: A library for hybrid CPU-GPU algebraic multigrid and preconditioned iterative methods (2020) arXiv
  18. Wathen, Michael; Greif, Chen: A scalable approximate inverse block preconditioner for an incompressible magnetohydrodynamics model problem (2020)
  19. Yushu, Dewen; Matouš, Karel: The image-based multiscale multigrid solver, preconditioner, and reduced order model (2020)
  20. Bello-Maldonado, Pedro D.; Fischer, Paul F.: Scalable low-order finite element preconditioners for high-order spectral element Poisson solvers (2019)

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