SuperLU is a general purpose library for the direct solution of large, sparse, nonsymmetric systems of linear equations on high performance machines. The library is written in C and is callable from either C or Fortran. The library routines will perform an LU decomposition with partial pivoting and triangular system solves through forward and back substitution. The LU factorization routines can handle non-square matrices but the triangular solves are performed only for square matrices. The matrix columns may be preordered (before factorization) either through library or user supplied routines. This preordering for sparsity is completely separate from the factorization. Working precision iterative refinement subroutines are provided for improved backward stability. Routines are also provided to equilibrate the system, estimate the condition number, calculate the relative backward error, and estimate error bounds for the refined solutions.

This software is also referenced in ORMS.

References in zbMATH (referenced in 137 articles , 2 standard articles )

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  1. Droniou, Jérôme; Hennicker, Julian; Masson, Roland: Numerical analysis of a two-phase flow discrete fracture matrix model (2019)
  2. Gander, Martin J.; Zhang, Hui: A class of iterative solvers for the Helmholtz equation: factorizations, sweeping preconditioners, source transfer, single layer potentials, polarized traces, and optimized Schwarz methods (2019)
  3. Ammon, Martin; Baggioli, Matteo; Jiménez-Alba, Amadeo; Moeckel, Sebastian: A smeared quantum phase transition in disordered holography (2018)
  4. Birgle, N.; Masson, R.; Trenty, L.: A domain decomposition method to couple nonisothermal compositional gas liquid Darcy and free gas flows (2018)
  5. Breit, Markus; Queisser, Gillian: What is required for neuronal calcium waves? A numerical parameter study (2018)
  6. Buhr, Andreas; Smetana, Kathrin: Randomized local model order reduction (2018)
  7. D’ambra, Pasqua; Filippone, Salvatore; Vassilevski, Panayot S.: BootCMatch. A software package for bootstrap AMG based on graph weighted matching (2018)
  8. Druinsky, Alex; Carlebach, Eyal; Toledo, Sivan: Wilkinson’s inertia-revealing factorization and its application to sparse matrices. (2018)
  9. Helenbrook, B. T.; Hrdina, J.: High-order adaptive arbitrary-Lagrangian-Eulerian (ALE) simulations of solidification (2018)
  10. Hoehme, Stefan; Bertaux, Francois; Weens, William; Grasl-Kraupp, Bettina; Hengstler, Jan G.; Drasdo, Dirk: Model prediction and validation of an order mechanism controlling the spatiotemporal phenotype of early hepatocellular carcinoma (2018)
  11. Mezzadri, Francesco; Galligani, Emanuele: An inexact Newton method for solving complementarity problems in hydrodynamic lubrication (2018)
  12. Sanderson, Conrad; Curtin, Ryan: A user-friendly hybrid sparse matrix class in C++ (2018)
  13. Schneider, Martin; Flemisch, B.; Helmig, R.; Terekhov, K.; Tchelepi, H.: Monotone nonlinear finite-volume method for challenging grids (2018)
  14. Shabat, Gil; Shmueli, Yaniv; Aizenbud, Yariv; Averbuch, Amir: Randomized LU decomposition (2018)
  15. Torun, F. Sukru; Manguoglu, Murat; Aykanat, Cevdet: A novel partitioning method for accelerating the block Cimmino algorithm (2018)
  16. Walker, Shawn W.: FELICITY: a Matlab/C++ toolbox for developing finite element methods and simulation modeling (2018)
  17. Adams, Mark F.; Hirvijoki, Eero; Knepley, Matthew G.; Brown, Jed; Isaac, Tobin; Mills, Richard: Landau collision integral solver with adaptive mesh refinement on emerging architectures (2017)
  18. Batty, Christopher: A cell-centred finite volume method for the Poisson problem on non-graded quadtrees with second order accurate gradients (2017)
  19. Chaillat, Stéphanie; Darbas, Marion; Le Louër, Frédérique: Fast iterative boundary element methods for high-frequency scattering problems in 3D elastodynamics (2017)
  20. Filbet, Francis; Herda, Maxime: A finite volume scheme for boundary-driven convection-diffusion equations with relative entropy structure (2017)

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