AMD

Algorithm 837: AMD is a set of routines that implements the approximate minimum degree ordering algorithm to permute sparse matrices prior to numerical factorization. There are versions written in both C and Fortran 77. A MATLAB interface is included.

Keywords for this software

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References in zbMATH (referenced in 51 articles , 1 standard article )

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  1. Axelsson, Owe; Liang, Zhao-Zheng: Parameter modified versions of preconditioning and iterative inner product free refinement methods for two-by-two block matrices (2019)
  2. Berger-Vergiat, Luc; Chen, Xiaocui; Waisman, Haim: Explicit and implicit methods for shear band modeling at high strain rates (2019)
  3. Dillon, Geoffrey; Kalantzis, Vassilis; Xi, Yuanzhe; Saad, Yousef: A hierarchical low rank Schur complement preconditioner for indefinite linear systems (2018)
  4. Duff, Iain; Hogg, Jonathan; Lopez, Florent: Experiments with sparse Cholesky using a sequential task-flow implementation (2018)
  5. Peng, Wei; Wang, Hongxia: A general scheme for log-determinant computation of matrices via stochastic polynomial approximation (2018)
  6. Xi, Yuanzhe; Li, Ruipeng; Saad, Yousef: Fast computation of spectral densities for generalized eigenvalue problems (2018)
  7. Yamashita, Makoto; Mullin, Tim J.; Safarina, Sena: An efficient second-order cone programming approach for optimal selection in tree breeding (2018)
  8. Li, Ruipeng; Saad, Yousef: Low-rank correction methods for algebraic domain decomposition preconditioners (2017)
  9. Suñagua, Porfirio; Oliveira, Aurelio R. L.: A new approach for finding a basis for the splitting preconditioner for linear systems from interior point methods (2017)
  10. Xi, Yuanzhe; Saad, Yousef: A rational function preconditioner for indefinite sparse linear systems (2017)
  11. Zhang, Ke; Zhang, Ju-Li; Gu, Chuan-Qing: A new relaxed PSS preconditioner for nonsymmetric saddle point problems (2017)
  12. Berger-Vergiat, Luc; McAuliffe, Colin; Waisman, Haim: Parallel preconditioners for monolithic solution of shear bands (2016)
  13. Bertaccini, Daniele; Filippone, Salvatore: Sparse approximate inverse preconditioners on high performance GPU platforms (2016)
  14. Cannataro, Begüm Şenses; Rao, Anil V.; Davis, Timothy A.: State-defect constraint pairing graph coarsening method for Karush-Kuhn-Tucker matrices arising in orthogonal collocation methods for optimal control (2016)
  15. Hogg, Jonathan D.; Ovtchinnikov, Evgueni; Scott, Jennifer A.: A sparse symmetric indefinite direct solver for GPU architectures (2016)
  16. O’Donoghue, Brendan; Chu, Eric; Parikh, Neal; Boyd, Stephen: Conic optimization via operator splitting and homogeneous self-dual embedding (2016)
  17. Xi, Yuanzhe; Li, Ruipeng; Saad, Yousef: An algebraic multilevel preconditioner with low-rank corrections for sparse symmetric matrices (2016)
  18. Dassios, Ioannis; Fountoulakis, Kimon; Gondzio, Jacek: A preconditioner for a primal-dual Newton conjugate gradient method for compressed sensing problems (2015)
  19. Aposporidis, Alexis; Vassilevski, Panayot S.; Veneziani, Alessandro: Multigrid preconditioning of the non-regularized augmented Bingham fluid problem (2014)
  20. Parikh, Neal; Boyd, Stephen: Block splitting for distributed optimization (2014)

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