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.
This software is also referenced in ORMS.
Keywords for this software
References in zbMATH (referenced in 179 articles , 2 standard articles )
Showing results 1 to 20 of 179.
- Bollhöfer, Matthias; Schenk, Olaf; Verbosio, Fabio: A high performance level-block approximate LU factorization preconditioner algorithm (2021)
- Farrell, Patrick E.; Mitchell, Lawrence; Scott, L. Ridgway; Wechsung, Florian: A Reynolds-robust preconditioner for the Scott-Vogelius discretization of the stationary incompressible Navier-Stokes equations (2021)
- Gaillard, Antoine; Keeler, Jack S.; Le Lay, Grégoire; Lemoult, Grégoire; Thompson, Alice B.; Hazel, Andrew L.; Juel, Anne: The life and fate of a bubble in a geometrically perturbed Hele-Shaw channel (2021)
- Jolivet, Pierre; Roman, Jose E.; Zampini, Stefano: KSPHPDDM and PCHPDDM: extending PETSc with advanced Krylov methods and robust multilevel overlapping Schwarz preconditioners (2021)
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- Beams, Natalie N.; Gillman, Adrianna; Hewett, Russell J.: A parallel shared-memory implementation of a high-order accurate solution technique for variable coefficient Helmholtz problems (2020)
- Bollhöfer, Matthias; Schenk, Olaf; Janalik, Radim; Hamm, Steve; Gullapalli, Kiran: State-of-the-art sparse direct solvers (2020)
- Dutra do Carmo, E. G.; Leal, R. M. T.; Mansur, W. J.: A new scheme to obtain pollution-free solution for plane waves and to generate a continuous Petrov-Galerkin method for the Helmholtz problem (2020)
- Etling, Tommy; Herzog, Roland; Loayza, Estefanía; Wachsmuth, Gerd: First and second order shape optimization based on restricted mesh deformations (2020)
- Glusa, Christian; Boman, Erik G.; Chow, Edmond; Rajamanickam, Sivasankaran; Szyld, Daniel B.: Scalable asynchronous domain decomposition solvers (2020)
- Herrmann, Lukas; Kirchner, Kristin; Schwab, Christoph: Multilevel approximation of Gaussian random fields: fast simulation (2020)
- Reguly, István Z.; Mudalige, Gihan R.: Productivity, performance, and portability for computational fluid dynamics applications (2020)
- Sander, Oliver: DUNE -- the distributed and unified numerics environment (2020)
- Vassilevski, Yuri; Terekhov, Kirill; Nikitin, Kirill; Kapyrin, Ivan: Parallel finite volume computation on general meshes (2020)
- Wittum, Rebecca; Naegel, Arne; Heisig, Michael; Wittum, Gabriel: Mathematical modelling of the viable epidermis: impact of cell shape and vertical arrangement (2020)
- Amestoy, Patrick R.; Buttari, Alfredo; L’Excellent, Jean-Yves; Mary, Theo A.: Bridging the gap between flat and hierarchical low-rank matrix formats: the multilevel block low-rank format (2019)
- Bhattacharya, Rabi; Lin, Lizhen: Differential geometry for model independent analysis of images and other non-Euclidean data: recent developments (2019)
- Bootland, Niall; Bentley, Alistair; Kees, Christopher; Wathen, Andrew: Preconditioners for two-phase incompressible Navier-Stokes flow (2019)
- D’Ambra, Pasqua; Vassilevski, Panayot S.: Improving solve time of aggregation-based adaptive AMG. (2019)
- Droniou, Jérôme; Hennicker, Julian; Masson, Roland: Numerical analysis of a two-phase flow discrete fracture matrix model (2019)