CHOLMOD

Algorithm 887: CHOLMOD, Supernodal Sparse Cholesky Factorization and Update/Downdate. CHOLMOD is a set of routines for factorizing sparse symmetric positive definite matrices of the form A or AAT, updating/downdating a sparse Cholesky factorization, solving linear systems, updating/downdating the solution to the triangular system Lx = b, and many other sparse matrix functions for both symmetric and unsymmetric matrices. Its supernodal Cholesky factorization relies on LAPACK and the Level-3 BLAS, and obtains a substantial fraction of the peak performance of the BLAS. Both real and complex matrices are supported. CHOLMOD is written in ANSI/ISO C, with both C and MATLABTM interfaces. It appears in MATLAB 7.2 as x = A when A is sparse symmetric positive definite, as well as in several other sparse matrix functions. (Source: http://dl.acm.org/)


References in zbMATH (referenced in 102 articles , 1 standard article )

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  1. Antonietti, Paola F.; De Ponti, Jacopo; Formaggia, Luca; Scotti, Anna: Preconditioning techniques for the numerical solution of flow in fractured porous media (2021)
  2. Kozdon, Jeremy E.; Erickson, Brittany A.; Wilcox, Lucas C.: Hybridized summation-by-parts finite difference methods (2021)
  3. Luo, Zhao Tang; Sang, Huiyan; Mallick, Bani: A Bayesian contiguous partitioning method for learning clustered latent variables (2021)
  4. Rojas, Sergio; Pardo, David; Behnoudfar, Pouria; Calo, Victor M.: Goal-oriented adaptivity for a conforming residual minimization method in a dual discontinuous Galerkin norm (2021)
  5. Xi, Chenyang; Zheng, Hui: Improving the generalized Bloch mode synthesis method using algebraic condensation (2021)
  6. Anita K. Nandi, Tim C. D. Lucas, Rohan Arambepola, Peter Gething, Daniel J. Weiss: disaggregation: An R Package for Bayesian Spatial Disaggregation Modelling (2020) arXiv
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  8. Calo, Victor M.; Ern, Alexandre; Muga, Ignacio; Rojas, Sergio: An adaptive stabilized conforming finite element method via residual minimization on dual discontinuous Galerkin norms (2020)
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  10. Glusa, Christian; Boman, Erik G.; Chow, Edmond; Rajamanickam, Sivasankaran; Szyld, Daniel B.: Scalable asynchronous domain decomposition solvers (2020)
  11. Hartwig Anzt, Terry Cojean, Yen-Chen Chen, Goran Flegar, Fritz Göbel, Thomas Grützmacher, Pratik Nayak, Tobias Ribizel, Yu-Hsiang Tsai: Ginkgo: A high performance numerical linear algebra library (2020) not zbMATH
  12. Klockiewicz, Bazyli; Darve, Eric: Sparse hierarchical preconditioners using piecewise smooth approximations of eigenvectors (2020)
  13. Liu, Xiao; Xia, Jianlin; de Hoop, Maarten: Fast factorization update for general elliptic equations under multiple coefficient updates (2020)
  14. Nigam, Nilima; Siudeja, Bartłomiej; Young, Benjamin: A proof via finite elements for Schiffer’s conjecture on a regular pentagon (2020)
  15. Sander, Oliver: DUNE -- the distributed and unified numerics environment (2020)
  16. Sassen, Josua; Heeren, Behrend; Hildebrandt, Klaus; Rumpf, Martin: Geometric optimization using nonlinear rotation-invariant coordinates (2020)
  17. Yeung, Yu-Hong; Pothen, Alex; Crouch, Jessica: AMPS: Real-time mesh cutting with augmented matrices for surgical simulations. (2020)
  18. Bollhöfer, Matthias; Eftekhari, Aryan; Scheidegger, Simon; Schenk, Olaf: Large-scale sparse inverse covariance matrix estimation (2019)
  19. Hardin, Thomas J.: Accelerating coupled finite element-kinetic Monte Carlo models: (200 \times) speedup of shear transformation zone dynamics simulations (2019)
  20. Howse, Alexander J.; de Sterck, Hans; Falgout, Robert D.; MacLachlan, Scott; Schroder, Jacob: Parallel-in-time multigrid with adaptive spatial coarsening for the linear advection and inviscid Burgers equations (2019)

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