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Visible to Intel only — GUID: GUID-E7B1FAE4-4AA3-4886-BCAB-0C09FD8FDB27
Singular Value Decomposition: ScaLAPACK Driver Routines
This section describes ScaLAPACK routines for computing the singular value decomposition (SVD) of a general m-by-n matrix A (see LAPACK"Singular Value Decomposition" ).
To find the SVD of a general matrix A, this matrix is first reduced to a bidiagonal matrix B by a unitary (orthogonal) transformation, and then SVD of the bidiagonal matrix is computed. Note that the SVD of B is computed using the LAPACK routine ?bdsqr .
Table "Computational Routines for Singular Value Decomposition (SVD)" lists ScaLAPACK computational routines for performing this decomposition.