- Referenced in 371 articles
- ANSI C code for sparse LU factorization is presented that combines a column pre-ordering ... ordering and analyzing a sparse matrix, computing the numerical factorization, solving a system with ... factors, transposing and permuting a sparse matrix, and converting between sparse matrix representations.\parThe simple ... from the details of the complex sparse factorization data structures by returning simple handles...
- Referenced in 442 articles
- basis package (for maintaining sparse LU factors of the basis matrix), automatic scaling of linear...
- Referenced in 1647 articles
- factorizations and estimating condition numbers. Dense and banded matrices are handled, but not general sparse...
- Referenced in 158 articles
- Efficient MATLAB computations with sparse and factored tensors. The term tensor refers simply ... efficient storage and computation. First, we study sparse tensors, which have the property that ... elements are zero. We propose storing sparse tensors using coordinate format and describe the computational ... tensor (which itself may be dense, sparse, or factored) and a matrix along each mode...
- Referenced in 100 articles
- Algorithm 887: CHOLMOD, Supernodal Sparse Cholesky Factorization and Update/Downdate. CHOLMOD ... routines for factorizing sparse symmetric positive definite matrices of the form A or AAT, updating/downdating ... sparse Cholesky factorization, solving linear systems, updating/downdating the solution to the triangular system ... other sparse matrix functions for both symmetric and unsymmetric matrices. Its supernodal Cholesky factorization relies...
- Referenced in 81 articles
- ﬁles from two Fortran packages: a sparse Cholesky factorization package developed by Esmond...
- Referenced in 381 articles
- symrcm: Sparse reverse Cuthill-McKee ordering. r = symrcm(S) returns the symmetric reverse Cuthill-McKee ... good preordering for LU or Cholesky factorization of matrices that come from long, skinny problems ... nonsymmetric S. For a real, symmetric sparse matrix, S, the eigenvalues...
- Referenced in 29 articles
- SuiteSparseQR: Multifrontal multithreaded rank-revealing sparse QR factorization SuiteSparseQR is a sparse QR factorization package ... sufficiently large problems, the resulting sparse QR factorization obtains a substantial fraction of the theoretical...
- Referenced in 29 articles
- prior to numerical factorization, and (2) sparse Cholesky factorization, which requires a symmetric permutation ... rows and columns of the matrix being factorized. These orderings are computed by COLAMD ... from COLAMD is also suitable for sparse QR factorization, and the factorization of matrices...
- Referenced in 35 articles
- decomposition of a covariance matrix into sparse factors, and has wide applications ranging from biology ... arising in the direct sparse PCA method...
- Referenced in 42 articles
- factored in PCG using a sparse modified Cholesky factorization based on the Yale Sparse Matrix...
- Referenced in 31 articles
- TAUCS: a library of sparse linear solvers. The current version of the library (1.0) includes ... Factorization. This code is quite fast (several times faster than Matlab 6’s sparse Cholesky ... Core, Left-Looking Supernodal Sparse Cholesky Factorization. Solves huge systems by storing the Cholesky factors ... systems. Out-of-Core Sparse LU with Partial Pivoting Factor and Solve. Can solve huge...
- Referenced in 17 articles
- Sparse QR factorization in MATLAB In the recently presented sparse matrix extension of MATLAB, there ... routine for sparse QR factorization. Sparse linear least squares problems are instead solved ... describe a multifrontal method for sparse QR factorization and its implementation in MATLAB ... expensive, and the reformulation of the sparse problem into dense subproblems is advantageous. Using...
- Referenced in 26 articles
- definite matrices. It combines a generalized factored sparse approximate inverse (FSAI) with an incomplete...
- Referenced in 794 articles
- most appropriate for large sparse or structured matrices A where structured means that a matrix ... problems. For many standard problems, a matrix factorization is not required. Only the action...
- Referenced in 28 articles
- block partitioning and scheduling problem for sparse parallel factorization without pivoting is considered. There...
- Referenced in 16 articles
- Algorithm 849: A concise sparse Cholesky factorization package. The LDL software package ... short, concise routines for factorizing symmetric positive-definite sparse matrices, with some applicability to symmetric ... possible, including an elegant method of sparse symmetric factorization that computes the factorization...
- Referenced in 55 articles
- ordering algorithm to permute sparse matrices prior to numerical factorization. There are versions written...
- Referenced in 53 articles
- tensor factorizations with structured factors and support for dense, sparse and incomplete data sets, tensor...
- Referenced in 13 articles
- high performance FSAI preconditioning. The Factorized Sparse Approximate Inverse (FSAI) is an efficient technique ... symmetric positive definite sparse linear systems. The key factor controlling FSAI efficiency is the identification...