Direct methods for sparse linear systems. Computational scientists often encounter problems requiring the solution of sparse systems of linear equations. Attacking these problems efficiently requires an in-depth knowledge of the underlying theory, algorithms, and data structures found in sparse matrix software libraries. Here, Davis presents the fundamentals of sparse matrix algorithms to provide the requisite background. The book includes CSparse, a concise downloadable sparse matrix package that illustrates the algorithms and theorems presented in the book and equips readers with the tools necessary to understand larger and more complex software packages.par With a strong emphasis on MATLAB and the C programming language, Direct Methods for Sparse Linear Systems equips readers with the working knowledge required to use sparse solver packages and write code to interface applications to those packages. The book also explains how MATLAB performs its sparse matrix computations.

References in zbMATH (referenced in 218 articles , 1 standard article )

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  1. Anderson, Robert; Andrej, Julian; Barker, Andrew; Bramwell, Jamie; Camier, Jean-Sylvain; Cerveny, Jakub; Dobrev, Veselin; Dudouit, Yohann; Fisher, Aaron; Kolev, Tzanio; Pazner, Will; Stowell, Mark; Tomov, Vladimir; Akkerman, Ido; Dahm, Johann; Medina, David; Zampini, Stefano: MFEM: a modular finite element methods library (2021)
  2. Chen, Changxiong; Chen, Liping; Cheng, Xianjuan: An efficient method for determining fault isolability properties based on an augmented system model (2021)
  3. Corsaro, Stefania; De Simone, Valentina; Marino, Zelda: Split Bregman iteration for multi-period mean variance portfolio optimization (2021)
  4. Kahl, Karsten; Lang, Bruno: Hypergraph edge elimination -- a symbolic phase for Hermitian eigensolvers based on rank-1 modifications (2021)
  5. Kozdon, Jeremy E.; Erickson, Brittany A.; Wilcox, Lucas C.: Hybridized summation-by-parts finite difference methods (2021)
  6. Langer, Ulrich; Zank, Marco: Efficient direct space-time finite element solvers for parabolic initial-boundary value problems In anisotropic Sobolev spaces (2021)
  7. Lin, Tianyi; Ma, Shiqian; Ye, Yinyu; Zhang, Shuzhong: An ADMM-based interior-point method for large-scale linear programming (2021)
  8. Liu, Yang; Ghysels, Pieter; Claus, Lisa; Li, Xiaoye Sherry: Sparse approximate multifrontal factorization with butterfly compression for high-frequency wave equations (2021)
  9. Liu, Yang; Ghysels, Pieter; Claus, Lisa; Li, Xiaoye Sherry: Sparse approximate multifrontal factorization with butterfly compression for high-frequency wave equations (2021)
  10. O’Donoghue, Brendan: Operator splitting for a homogeneous embedding of the linear complementarity problem (2021)
  11. Thore, Carl-Johan: Topology optimization of Stokes flow with traction boundary conditions using low-order finite elements (2021)
  12. Bollhöfer, Matthias; Schenk, Olaf; Janalik, Radim; Hamm, Steve; Gullapalli, Kiran: State-of-the-art sparse direct solvers (2020)
  13. Buttari, Alfredo; Hauberg, Søren; Kodsi, Costy: Parallel \textitQRfactorization of block-tridiagonal matrices (2020)
  14. Carrera, Barbara; Mok, Chin Man; Papaioannou, Iason: Efficient estimation of hydraulic conductivity heterogeneity with non-redundant measurement information (2020)
  15. da Silva, André Renato Villela; Ochi, Luiz Satoru; da Silva Barros, Bruno José; Pinheiro, Rian Gabriel S.: Efficient approaches for the flooding problem on graphs (2020)
  16. Dellar, O. J.; Jones, B. Ll.: Efficient frequency response computation for low-order modelling of spatially distributed systems (2020)
  17. Etter, Simon; Massatt, Daniel; Luskin, Mitchell; Ortner, Christoph: Modeling and computation of Kubo conductivity for two-dimensional incommensurate bilayers (2020)
  18. Geißler, Björn; Martin, Alexander; Morsi, Antonio; Walther, Maximilian; Kolb, Oliver; Lang, Jens; Wagner, Lisa: Optimization (2020)
  19. Groß, Michael; Dietzsch, Julian; Röbiger, Chris: Non-isothermal energy-momentum time integrations with drilling degrees of freedom of composites with viscoelastic fiber bundles and curvature-twist stiffness (2020)
  20. Gu, Xian-Ming; Zhao, Yanpu; Huang, Tingzhu; Zhao, Ran: Efficient preconditioned iterative linear solvers for 3-D magnetostatic problems using edge elements (2020)

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