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 81 articles , 1 standard article )

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  1. Berardocco, Luca; Kronbichler, Martin; Gravemeier, Volker: A hybridizable discontinuous Galerkin method for electromagnetics with a view on subsurface applications (2020)
  2. Çuğu, İlke; Manguoğlu, Murat: A parallel multithreaded sparse triangular linear system solver (2020)
  3. Bootland, Niall; Bentley, Alistair; Kees, Christopher; Wathen, Andrew: Preconditioners for two-phase incompressible Navier-Stokes flow (2019)
  4. Farrell, Patrick E.; Mitchell, Lawrence; Wechsung, Florian: An augmented Lagrangian preconditioner for the 3D stationary incompressible Navier-Stokes equations at High Reynolds number (2019)
  5. Hu, Xiukun; Douglas, Craig C.: Performance and scalability analysis of a coupled dual porosity Stokes model implemented with FEniCS (2019)
  6. Pothen, Alex; Ferdous, S. M.; Manne, Fredrik: Approximation algorithms in combinatorial scientific computing (2019)
  7. Scott, Jennifer A.; Tůma, Miroslav: Sparse stretching for solving sparse-dense linear least-squares problems (2019)
  8. Chávez, Gustavo; Turkiyyah, George; Zampini, Stefano; Keyes, David: Parallel accelerated cyclic reduction preconditioner for three-dimensional elliptic PDEs with variable coefficients (2018)
  9. Fang, Jun; Qian, Jianliang; Zepeda-Núñez, Leonardo; Zhao, Hongkai: A hybrid approach to solve the high-frequency Helmholtz equation with source singularity in smooth heterogeneous media (2018)
  10. Fohrmeister, Volker; Bartels, Alexander; Mosler, Jörn: Variational updates for thermomechanically coupled gradient-enhanced elastoplasticity -- implementation based on hyper-dual numbers (2018)
  11. Helenbrook, B. T.; Hrdina, J.: High-order adaptive arbitrary-Lagrangian-Eulerian (ALE) simulations of solidification (2018)
  12. Jacquelin, Mathias; Lin, Lin; Yang, Chao: \textttPselinv-- a distributed memory parallel algorithm for selected inversion, the symmetric case (2017)
  13. Peters, Franciane Conceição; Fontes Junior, Edivaldo Figueiredo; Mansur, Webe João; Soares Filho, Djalma Manoel; da Silva Garcia Monteiro, Cid; Carvalho, Pedro: An adaptive meshless parameterization for full waveform inversion (2017)
  14. Vašatová, Alena; Tomčala, Jiří; Sojka, Radim; Pecha, Marek; Kružík, Jakub; Horák, David; Hapla, Václav; Čermák, Martin: Parallel strategies for solving the FETI coarse problem in the PERMON toolbox. (2017)
  15. Xin, Zixing; Xia, Jianlin; de Hoop, Maarten V.; Cauley, Stephen; Balakrishnan, Venkataramanan: A distributed-memory randomized structured multifrontal method for sparse direct solutions (2017)
  16. Feldman, Yuri; Gulberg, Yosef: An extension of the immersed boundary method based on the distributed Lagrange multiplier approach (2016)
  17. Gholami, Amir; Malhotra, Dhairya; Sundar, Hari; Biros, George: FFT, FMM, or multigrid? A comparative study of state-of-the-art Poisson solvers for uniform and nonuniform grids in the unit cube (2016)
  18. Mathias Jacquelin, Yili Zheng, Esmond Ng, Katherine Yelick: An Asynchronous Task-based Fan-Both Sparse Cholesky Solver (2016) arXiv
  19. Wang, Shen; Li, Xiaoye S.; Rouet, François-Henry; Xia, Jianlin; De Hoop, Maarten V.: A parallel geometric multifrontal solver using hierarchically semiseparable structure (2016)
  20. Amestoy, Patrick; Ashcraft, Cleve; Boiteau, Olivier; Buttari, Alfredo; L’Excellent, Jean-Yves; Weisbecker, Clément: Improving multifrontal methods by means of block low-rank representations (2015)

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