Provides singular value decomposition using a block-based approach. Experimental. More...
#include <boost/numeric/ublas/vector.hpp>
#include <boost/numeric/ublas/matrix.hpp>
#include <cmath>
#include "viennacl/matrix.hpp"
#include "viennacl/linalg/opencl/kernels/svd.hpp"
#include "viennacl/linalg/qr-method-common.hpp"
Go to the source code of this file.
Namespaces | |
viennacl | |
Main namespace in ViennaCL. Holds all the basic types such as vector, matrix, etc. and defines operations upon them. | |
viennacl::linalg | |
Provides all linear algebra operations which are not covered by operator overloads. | |
viennacl::linalg::detail | |
Namespace holding implementation details for linear algebra routines. Usually not of interest for a library user. | |
Functions | |
template<typename MatrixType , typename VectorType > | |
void | viennacl::linalg::detail::givens_prev (MatrixType &matrix, VectorType &tmp1, VectorType &tmp2, int n, int l, int k) |
template<typename MatrixType , typename VectorType > | |
void | viennacl::linalg::detail::change_signs (MatrixType &matrix, VectorType &signs, int n) |
template<typename MatrixType , typename CPU_VectorType > | |
void | viennacl::linalg::detail::svd_qr_shift (MatrixType &vcl_u, MatrixType &vcl_v, CPU_VectorType &q, CPU_VectorType &e) |
template<typename SCALARTYPE , unsigned int ALIGNMENT> | |
bool | viennacl::linalg::detail::householder_c (viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &A, viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &Q, viennacl::vector< SCALARTYPE, ALIGNMENT > &D, vcl_size_t row_start, vcl_size_t col_start) |
template<typename SCALARTYPE , unsigned int ALIGNMENT> | |
bool | viennacl::linalg::detail::householder_r (viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &A, viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &Q, viennacl::vector< SCALARTYPE, ALIGNMENT > &D, vcl_size_t row_start, vcl_size_t col_start) |
template<typename SCALARTYPE , unsigned int ALIGNMENT> | |
void | viennacl::linalg::detail::bidiag (viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &Ai, viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &QL, viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &QR) |
template<typename SCALARTYPE , unsigned int ALIGNMENT> | |
void | viennacl::linalg::svd (viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &A, viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &QL, viennacl::matrix< SCALARTYPE, row_major, ALIGNMENT > &QR) |
Computes the singular value decomposition of a matrix A. Experimental in 1.3.x. More... | |
Provides singular value decomposition using a block-based approach. Experimental.
Contributed by Volodymyr Kysenko.
Definition in file svd.hpp.