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. Wang, Kun; Liu, Hui; Luo, Jia; Chen, Zhangxin: Efficient CPR-type preconditioner and its adaptive strategies for large-scale parallel reservoir simulations (2018)
  2. Allen, Jeffery; Leibs, Chris; Manteuffel, Tom; Rajaram, Harihar: A fluidity-based first-order system least-squares method for ice sheets (2017)
  3. Bauer, S.; Mohr, M.; Rüde, U.; Weismüller, J.; Wittmann, M.; Wohlmuth, B.: A two-scale approach for efficient on-the-fly operator assembly in massively parallel high performance multigrid codes (2017)
  4. Carsten Burstedde, Jose A. Fonseca, Stefan Kollet: Enhancing speed and scalability of the ParFlow simulation code (2017) arXiv
  5. Chávez, Gustavo; Turkiyyah, George; Keyes, David E.: A direct elliptic solver based on hierarchically low-rank Schur complements (2017)
  6. Jomo, John N.; Zander, Nils; Elhaddad, Mohamed; Özcan, Ali; Kollmannsberger, Stefan; Mundani, Ralf-Peter; Rank, Ernst: Parallelization of the multi-level $hp$-adaptive finite cell method (2017)
  7. Koblitz, A.R.; Lovett, S.; Nikiforakis, N.; Henshaw, W.D.: Direct numerical simulation of particulate flows with an overset grid method (2017)
  8. Kong, Fande; Cai, Xiao-Chuan: A scalable nonlinear fluid-structure interaction solver based on a Schwarz preconditioner with isogeometric unstructured coarse spaces in 3D (2017)
  9. la Cour Christensen, Max; Villa, Umberto; Engsig-Karup, Allan P.; Vassilevski, Panayot S.: Numerical multilevel upscaling for incompressible flow in reservoir simulation: an element-based algebraic multigrid (amge) approach (2017)
  10. Maddison, J.R.; Hiester, H.R.: Optimal constrained interpolation in mesh-adaptive finite element modeling (2017)
  11. Mardal, Kent-André; Nielsen, Bjørn Fredrik; Nordaas, Magne: Robust preconditioners for PDE-constrained optimization with limited observations (2017)
  12. Neumüller, Martin; Vassilevski, Panayot S.; Villa, Umberto E.: Space-time CFOSLS methods with AMGe upscaling (2017)
  13. Vittoz, Louis; Oger, Guillaume; Li, Zhe; De Leffe, Matthieu; Le Touzé, David: A high-order finite volume solver on locally refined Cartesian meshes -- benchmark session (2017)
  14. Berger-Vergiat, Luc; McAuliffe, Colin; Waisman, Haim: Parallel preconditioners for monolithic solution of shear bands (2016)
  15. Bienz, Amanda; Falgout, Robert D.; Gropp, William; Olson, Luke N.; Schroder, Jacob B.: Reducing parallel communication in algebraic multigrid through sparsification (2016)
  16. Christon, Mark A.; Bakosi, Jozsef; Nadiga, Balasubramanya T.; Berndt, Markus; Francois, Marianne M.; Stagg, Alan K.; Xia, Yidong; Luo, Hong: A hybrid incremental projection method for thermal-hydraulics applications (2016)
  17. Ervik, Åsmund; Lysgaard, Morten Olsen; Herdes, Carmelo; Jiménez-Serratos, Guadalupe; Müller, Erich A.; Munkejord, Svend Tollak; Müller, Bernhard: A multiscale method for simulating fluid interfaces covered with large molecules such as asphaltenes (2016)
  18. Gander, Martin J.; Neumüller, Martin: Analysis of a new space-time parallel multigrid algorithm for parabolic problems (2016)
  19. Gratton, Serge; Hénon, Pascal; Jiránek, Pavel; Vasseur, Xavier: Reducing complexity of algebraic multigrid by aggregation. (2016)
  20. Huber, Markus; Gmeiner, Björn; Rüde, Ulrich; Wohlmuth, Barbara: Resilience for massively parallel multigrid solvers (2016)

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