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 150 articles , 2 standard articles )
Showing results 1 to 20 of 150.
- Reguly, István Z.; Mudalige, Gihan R.: Productivity, performance, and portability for computational fluid dynamics applications (2020)
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- Droniou, Jérôme; Hennicker, Julian; Masson, Roland: Numerical analysis of a two-phase flow discrete fracture matrix model (2019)
- Farrell, Patrick E.; Mitchell, Lawrence; Wechsung, Florian: An augmented Lagrangian preconditioner for the 3D stationary incompressible Navier-Stokes equations at High Reynolds number (2019)
- Fu, Shubin; Gao, Kai; Gibson, Richard L. jun.; Chung, Eric T.: An efficient high-order multiscale finite element method for frequency-domain elastic wave modeling (2019)
- 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)
- Jakob M. Maljaars, Chris N. Richardson, Nathan Sime: LEoPart: a particle library for FEniCS (2019) arXiv
- Jiang, J.; Garikipati, K.; Rudraraju, S.: A diffuse interface framework for modeling the evolution of multi-cell aggregates as a soft packing problem driven by the growth and division of cells (2019)
- Li, Xinge; Zhang, Yongjie Jessica; Yang, Xuyang; Xu, Haibo; Xu, Guoliang: Point cloud surface segmentation based on volumetric eigenfunctions of the Laplace-Beltrami operator (2019)
- Thomas, S. J.; Ananthan, S.; Yellapantula, S.; Hu, J. J.; Lawson, M.; Sprague, M. A.: A comparison of classical and aggregation-based algebraic multigrid preconditioners for high-fidelity simulation of Wind Turbine incompressible flows (2019)
- Ammon, Martin; Baggioli, Matteo; Jiménez-Alba, Amadeo; Moeckel, Sebastian: A smeared quantum phase transition in disordered holography (2018)
- Birgle, N.; Masson, R.; Trenty, L.: A domain decomposition method to couple nonisothermal compositional gas liquid Darcy and free gas flows (2018)
- Breit, Markus; Queisser, Gillian: What is required for neuronal calcium waves? A numerical parameter study (2018)
- Buhr, Andreas; Smetana, Kathrin: Randomized local model order reduction (2018)
- D’ambra, Pasqua; Filippone, Salvatore; Vassilevski, Panayot S.: BootCMatch. A software package for bootstrap AMG based on graph weighted matching (2018)
- Druinsky, Alex; Carlebach, Eyal; Toledo, Sivan: Wilkinson’s inertia-revealing factorization and its application to sparse matrices. (2018)
- Helenbrook, B. T.; Hrdina, J.: High-order adaptive arbitrary-Lagrangian-Eulerian (ALE) simulations of solidification (2018)
- 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)
- Mezzadri, Francesco; Galligani, Emanuele: An inexact Newton method for solving complementarity problems in hydrodynamic lubrication (2018)