- Referenced in 794 articles
- most appropriate for large sparse or structured matrices A where structured means that a matrix ... Shifted QR technique that is suitable for large scale problems. For many standard problems...
- Referenced in 646 articles
- Matrix Collection, a large and actively growing set of sparse matrices that arise in real...
- Referenced in 180 articles
- full, the action of a large sparse matrix exponential on an operand vector ... with constant inhomogeneity. The backbone of the sparse routines consists of matrix-free Krylov subspace ... capable of coping with sparse matrices of large dimension. The software handles real and complex...
- Referenced in 60 articles
- singular value decomposition (SVD) of large sparse matrices using double precision ANSI Fortran ... left- and right-singular vectors) for large sparse matrices. The package has been ported ... need to compute large rank approximations to sparse term-document matrices from information retrieval applications ... used, for example, to handle extremely large sparse matrices (on the order of a million...
- Referenced in 495 articles
- computing pseudospectra of dense and sparse matrices. It also provides a graphical interface to MATLAB ... built-in eigs routine (ARPACK) for large-scale eigenvalue computations...
- Referenced in 57 articles
- both with full matrices and with large sparse matrices, and makes use of many advanced...
- Referenced in 580 articles
- matrix pencil A-lambda*B. The matrices can be real or complex, Hermitian ... case A and B are sparse and of large size. The Jacobi-Davidson method...
- Referenced in 63 articles
- current estimate. For large matrices there is a special sparse-matrix class named ”Incomplete” that ... computing low-rank SVDs on large sparse centered matrices (i.e. principal components...
- Referenced in 104 articles
- singular value decomposition of large and sparse or structured matrices. The SVD routines are based...
- Referenced in 45 articles
- separate routines for dense and sparse Jacobian matrices. A high level driver for the special ... iterative algorithms for large sparse Jacobian matrices...
- Referenced in 23 articles
- least squares methods for problems with sparse design matrices. Significant performance improvements in memory utilization ... speed are possible for applications involving large sparse matrices...
- Referenced in 131 articles
- computing fill-reducing orderings of sparse matrices. ParMETIS extends the functionality provided by METIS ... especially suited for parallel AMR computations and large scale numerical simulations. The algorithms implemented...
- Referenced in 47 articles
- efficiently solving large systems of linear equations whose coefficient matrices are sparse. This high-performance...
- Referenced in 11 articles
- singular triplets of large, sparse matrices is a challenging task, especially when the smallest magnitude...
- Referenced in 18 articles
- computing selected eigenvalues of large sparse symmetric matrices A new software code for computing selected...
- Referenced in 47 articles
- solving large systems of linear algebraic equations with sparse coefficient matrices. The emphasis...
- Referenced in 179 articles
- library for the direct solution of large, sparse, nonsymmetric systems of linear equations on high ... factorization routines can handle non-square matrices but the triangular solves are performed only...
- Referenced in 7 articles
- Principal Components Analysis for Large Dense and Sparse Matrices. Fast and memory efficient methods ... principal components analysis of large sparse and dense matrices...
- Referenced in 5 articles
- allows one in particular to handle large sparse matrices. It also has an experimental part...