LDL

Algorithm 849: A concise sparse Cholesky factorization package. The LDL software package is a set of short, concise routines for factorizing symmetric positive-definite sparse matrices, with some applicability to symmetric indefinite matrices. Its primary purpose is to illustrate much of the basic theory of sparse matrix algorithms in as concise a code as possible, including an elegant method of sparse symmetric factorization that computes the factorization row-by-row but stores it column-by-column. The entire symbolic and numeric factorization consists of less than 50 executable lines of code. The package is written in C, and includes a MATLAB interface. (Source: http://dl.acm.org/)

This software is also peer reviewed by journal TOMS.


References in zbMATH (referenced in 19 articles , 1 standard article )

Showing results 1 to 19 of 19.
Sorted by year (citations)

  1. Ebenbeck, Matthias; Garcke, Harald; Nürnberg, Robert: Cahn-Hilliard-Brinkman systems for tumour growth (2021)
  2. Lin, Tianyi; Ma, Shiqian; Ye, Yinyu; Zhang, Shuzhong: An ADMM-based interior-point method for large-scale linear programming (2021)
  3. Ben Hermans, Andreas Themelis, Panagiotis Patrinos: QPALM: A Proximal Augmented Lagrangian Method for Nonconvex Quadratic Programs (2020) arXiv
  4. Orban, Dominique; Siqueira, Abel Soares: A regularization method for constrained nonlinear least squares (2020)
  5. Stellato, Bartolomeo; Banjac, Goran; Goulart, Paul; Bemporad, Alberto; Boyd, Stephen: OSQP: an operator splitting solver for quadratic programs (2020)
  6. Nürnberg, Robert; Tucker, Edward J. W.: Stable finite element approximation of a Cahn-Hilliard-Stokes system coupled to an electric field (2017)
  7. Sencer Nuri Yeralan; Timothy A. Davis; Wissam M. Sid-Lakhdar; Sanjay Ranka: Algorithm 980: Sparse QR Factorization on the GPU (2017) not zbMATH
  8. Yeralan, Sencer Nuri; Davis, Timothy A.; Sid-Lakhdar, Wissam M.; Ranka, Sanjay: Algorithm 980: Sparse QR factorization on the GPU (2017)
  9. O’Donoghue, Brendan; Chu, Eric; Parikh, Neal; Boyd, Stephen: Conic optimization via operator splitting and homogeneous self-dual embedding (2016)
  10. Aposporidis, Alexis; Vassilevski, Panayot S.; Veneziani, Alessandro: Multigrid preconditioning of the non-regularized augmented Bingham fluid problem (2014)
  11. Parikh, Neal; Boyd, Stephen: Block splitting for distributed optimization (2014)
  12. Cai, Yunfeng; Bai, Zhaojun; Pask, John E.; Sukumar, N.: Hybrid preconditioning for iterative diagonalization of ill-conditioned generalized eigenvalue problems in electronic structure calculations (2013)
  13. Pereira, Fabio Henrique; Nabeta, Sílvio Ikuyo: A parallel wavelet-based algebraic multigrid black-box solver and preconditioner (2012)
  14. Barrett, John W.; Garcke, Harald; Nürnberg, Robert: On stable parametric finite element methods for the Stefan problem and the Mullins-Sekerka problem with applications to dendritic growth (2010)
  15. Lourakis, Manolis I. A.; Argyros, Antonis A.: SBA: a software package for generic sparse bundle adjustment (2009)
  16. Davis, Timothy A.; Hager, William W.: A sparse proximal implementation of the LP dual active set algorithm (2008)
  17. Davis, Timothy A.; Hager, William W.: Dual multilevel optimization (2008)
  18. Strauss, H. R.; Hientzsch, B.; Chen, J.: A spectral element implementation for the M3D extended MHD code (2008)
  19. Davis, Timothy A.: Algorithm 849: A concise sparse Cholesky factorization package. (2005)