Lines Matching full:sparse
214 // we process the sparse rhs per block of NbColsAtOnce columns temporarily stored into a dense matrix.
416 * \brief A sparse direct LU factorization and solver based on the PARDISO library
418 * This class allows to solve for A.X = B sparse linear problems via a direct LU factorization
419 * using the Intel MKL PARDISO library. The sparse matrix A must be squared and invertible.
420 * The vectors or matrices X and B can be either dense or sparse.
422 * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
466 * \brief A sparse direct Cholesky (LLT) factorization and solver based on the PARDISO library
468 * This class allows to solve for A.X = B sparse linear problems via a LL^T Cholesky factorization
469 * using the Intel MKL PARDISO library. The sparse matrix A must be selfajoint and positive definite.
470 * The vectors or matrices X and B can be either dense or sparse.
472 * \tparam MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
525 * \brief A sparse direct Cholesky (LDLT) factorization and solver based on the PARDISO library
527 * This class allows to solve for A.X = B sparse linear problems via a LDL^T Cholesky factorization
528 * using the Intel MKL PARDISO library. The sparse matrix A is assumed to be selfajoint and positive definite.
530 * The vectors or matrices X and B can be either dense or sparse.
532 * \tparam MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
