Developer Reference

Intel® oneAPI Math Kernel Library LAPACK Examples

ID 766877
Date 12/20/2021

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SGESDD Example

The routine computes the singular value decomposition (SVD) of a rectangular real matrix A, optionally the left and/or right singular vectors. This routine uses a divide and conquer algorithm to compute the SVD.

The SVD is written as:



  • A is a real m-by-n matrix.

  • SIGMA is an m-by-n matrix which is zero except for its min(m,n) diagonal elements.

  • U is an m-by-m orthogonal matrix.

  • VT (V transposed) is an n-by-n orthogonal matrix.

The diagonal elements of SIGMA are the singular values of A; they are real and non-negative, and are returned in descending order. The first min(m,n) columns of U and V are the left and right singular vectors of A.

The routine returns VT, not V.

C Interface

Please refer to the Matrix Layout section of the C Interface Conventions for the description of Row Major (C default) and Column Major (Fortran default).