- Referenced in 783 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 616 articles
- Matrix Collection, a large and actively growing set of sparse matrices that arise in real...
- Referenced in 173 articles
- exponential in full, the action of a large sparse matrix exponential on an operand vector ... capable of coping with sparse matrices of large dimension. The software handles real and complex...
- Referenced in 421 articles
- Solution of large linear systems with symmetric positive definite matrices; general symmetric matrices; general unsymmetric...
- Referenced in 586 articles
- large number of other useful functions to compute with mathematical entities such as matrices, power...
- 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 63 articles
- completed with the current estimate. For large matrices there is a special sparse-matrix class ... computing low-rank SVDs on large sparse centered matrices (i.e. principal components...
- Referenced in 476 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 572 articles
- matrix pencil A-lambda*B. The matrices can be real or complex, Hermitian ... sparse and of large size. The Jacobi-Davidson method is used to compute a partial...
- Referenced in 53 articles
- both with full matrices and with large sparse matrices, and makes use of many advanced...
- Referenced in 514 articles
- singular value decompositions of rectangular matrices and applies them to least-squares problems. LINPACK uses ... 1970s and early 1980s. LINPACK has been largely superceded by LAPACK, which has been designed...
- Referenced in 33 articles
- address the numerical problem of recovering large matrices of low rank when most...
- Referenced in 100 articles
- singular value decomposition of large and sparse or structured matrices. The SVD routines are based...
- Referenced in 77 articles
- obtain approximate eigenvalues of large non-Hermitian matrices. QMRPACK is a software package with Fortran...
- 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 22 articles
- 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 32 articles
- generalized eigenvalue problems. When the matrices are very large, iterative methods are used to generate...
- Referenced in 11 articles
- accurately computing singular triplets of large matrices. The computation of a few singular triplets ... large, sparse matrices is a challenging task, especially when the smallest magnitude singular values...
- Referenced in 128 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...