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LAPACKE_sgesdd Example Program in C for Column Major Data Layout
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/*
LAPACKE_sgesdd Example.
=======================
Program computes the singular value decomposition of a general
rectangular matrix A using a divide and conquer method, where A is:
7.52 -1.10 -7.95 1.08
-0.76 0.62 9.34 -7.10
5.13 6.62 -5.66 0.87
-4.75 8.52 5.75 5.30
1.33 4.91 -5.49 -3.52
-2.40 -6.77 2.34 3.95
Description.
============
The routine computes the singular value decomposition (SVD) of a real
m-by-n matrix A, optionally computing the left and/or right singular
vectors. If singular vectors are desired, it uses a divide and conquer
algorithm. The SVD is written as
A = U*SIGMA*VT
where 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 and 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.
Note that the routine returns VT, not V.
Example Program Results.
========================
LAPACKE_sgesdd (row-major, high-level) Example Program Results
Singular values
18.37 13.63 10.85 4.49
Left singular vectors (stored columnwise)
-0.57 0.18 0.01 0.53
0.46 -0.11 -0.72 0.42
-0.45 -0.41 0.00 0.36
0.33 -0.69 0.49 0.19
-0.32 -0.31 -0.28 -0.61
0.21 0.46 0.39 0.09
Right singular vectors (stored rowwise)
-0.52 -0.12 0.85 -0.03
0.08 -0.99 -0.09 -0.01
-0.28 -0.02 -0.14 0.95
0.81 0.01 0.50 0.31
*/
#include <stdlib.h>
#include <stdio.h>
#include "mkl_lapacke.h"
/* Auxiliary routines prototypes */
extern void print_matrix( char* desc, MKL_INT m, MKL_INT n, float* a, MKL_INT lda );
/* Parameters */
#define M 6
#define N 4
#define LDA N
#define LDU M
#define LDVT N
/* Main program */
int main() {
/* Locals */
MKL_INT m = M, n = N, lda = LDA, ldu = LDU, ldvt = LDVT, info;
/* Local arrays */
float s[N], u[LDU*M], vt[LDVT*N];
float a[LDA*M] = {
7.52f, -1.10f, -7.95f, 1.08f,
-0.76f, 0.62f, 9.34f, -7.10f,
5.13f, 6.62f, -5.66f, 0.87f,
-4.75f, 8.52f, 5.75f, 5.30f,
1.33f, 4.91f, -5.49f, -3.52f,
-2.40f, -6.77f, 2.34f, 3.95f
};
/* Executable statements */
printf( "LAPACKE_sgesdd (row-major, high-level) Example Program Results\n" );
/* Compute SVD */
info = LAPACKE_sgesdd( LAPACK_ROW_MAJOR, 'S', m, n, a, lda, s,
u, ldu, vt, ldvt );
/* Check for convergence */
if( info > 0 ) {
printf( "The algorithm computing SVD failed to converge.\n" );
exit( 1 );
}
/* Print singular values */
print_matrix( "Singular values", 1, n, s, 1 );
/* Print left singular vectors */
print_matrix( "Left singular vectors (stored columnwise)", m, n, u, ldu );
/* Print right singular vectors */
print_matrix( "Right singular vectors (stored rowwise)", n, n, vt, ldvt );
exit( 0 );
} /* End of LAPACKE_sgesdd Example */
/* Auxiliary routine: printing a matrix */
void print_matrix( char* desc, MKL_INT m, MKL_INT n, float* a, MKL_INT lda ) {
MKL_INT i, j;
printf( "\n %s\n", desc );
for( i = 0; i < m; i++ ) {
for( j = 0; j < n; j++ ) printf( " %6.2f", a[i*lda+j] );
printf( "\n" );
}
}
Parent topic: SGESDD Example