symamd
symamd: Symmetric approximate minimum degree permutation. p = symamd(S) for a symmetric positive definite matrix S, returns the permutation vector p such that S(p,p) tends to have a sparser Cholesky factor than S. To find the ordering for S, symamd constructs a matrix M such that spones(M’*M) = spones (S), and then computes p = colamd(M). The symamd function may also work well for symmetric indefinite matrices.
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References in zbMATH (referenced in 7 articles )
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Sorted by year (- Lourenco, Christopher; Escobedo, Adolfo R.; Moreno-Centeno, Erick; Davis, Timothy A.: Exact solution of sparse linear systems via left-looking roundoff-error-free Lu factorization in time proportional to arithmetic work (2019)
- Koppenol, Daniël C.; Vermolen, Fred J.; Koppenol-Gonzalez, Gabriela V.; Niessen, Frank B.; van Zuijlen, Paul P. M.; Vuik, Kees: A mathematical model for the simulation of the contraction of burns (2017)
- Ambikasaran, Sivaram: Generalized Rybicki Press algorithm. (2015)
- Davis, Timothy A.; Natarajan, E. Palamadai: Sparse matrix methods for circuit simulation problems (2012)
- Druinsky, Alex; Toledo, Sivan: Factoring matrices with a tree-structured sparsity pattern (2011)
- Davis, Timothy A.; Hager, William W.: A sparse proximal implementation of the LP dual active set algorithm (2008)
- Davis, Timothy A.; Gilbert, John R.; Larimore, Stefan I.; Ng, Esmond G.: Algorithm 836: COLAMD, a column approximate minimum degree ordering algorithm (2004)