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  • 12/20/2021
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LAPACKE_cgesvd Example Program in C for Row Major Data Layout

/******************************************************************************* * Copyright (C) 2009-2015 Intel Corporation. All Rights Reserved. * The information and material ("Material") provided below is owned by Intel * Corporation or its suppliers or licensors, and title to such Material remains * with Intel Corporation or its suppliers or licensors. The Material contains * proprietary information of Intel or its suppliers and licensors. The Material * is protected by worldwide copyright laws and treaty provisions. No part of * the Material may be copied, reproduced, published, uploaded, posted, * transmitted, or distributed in any way without Intel's prior express written * permission. No license under any patent, copyright or other intellectual * property rights in the Material is granted to or conferred upon you, either * expressly, by implication, inducement, estoppel or otherwise. Any license * under such intellectual property rights must be express and approved by Intel * in writing. * ******************************************************************************** */ /* LAPACKE_cgesvd Example. ======================= Program computes the singular value decomposition of a general rectangular complex matrix A: ( 5.91, -5.69) ( 7.09, 2.72) ( 7.78, -4.06) ( -0.79, -7.21) ( -3.15, -4.08) ( -1.89, 3.27) ( 4.57, -2.07) ( -3.88, -3.30) ( -4.89, 4.20) ( 4.10, -6.70) ( 3.28, -3.84) ( 3.84, 1.19) Description. ============ The routine computes the singular value decomposition (SVD) of a complex m-by-n matrix A, optionally computing the left and/or right singular vectors. The SVD is written as A = U*SIGMA*VH 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 unitary matrix and VH (V conjugate transposed) is an n-by-n unitary 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 VH, not V. Example Program Results. ======================== LAPACKE_cgesvd (row-major, high-level) Example Program Results Singular values 17.63 11.61 6.78 Left singular vectors (stored columnwise) ( -0.86, 0.00) ( 0.40, 0.00) ( 0.32, 0.00) ( -0.35, 0.13) ( -0.24, -0.21) ( -0.63, 0.60) ( 0.15, 0.32) ( 0.61, 0.61) ( -0.36, 0.10) Right singular vectors (stored rowwise) ( -0.22, 0.51) ( -0.37, -0.32) ( -0.53, 0.11) ( 0.15, 0.38) ( 0.31, 0.31) ( 0.09, -0.57) ( 0.18, -0.39) ( 0.38, -0.39) ( 0.53, 0.24) ( 0.49, 0.28) ( -0.47, -0.25) ( -0.15, 0.19) */ #include <stdlib.h> #include <stdio.h> #include "mkl_lapacke.h" #define min(a,b) ((a)>(b)?(b):(a)) /* Auxiliary routines prototypes */ extern void print_matrix( char* desc, MKL_INT m, MKL_INT n, MKL_Complex8* a, MKL_INT lda ); extern void print_rmatrix( char* desc, MKL_INT m, MKL_INT n, float* a, MKL_INT lda ); /* Parameters */ #define M 3 #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[M]; float superb[min(M,N)-1]; MKL_Complex8 u[LDU*M], vt[LDVT*N]; MKL_Complex8 a[LDA*M] = { { 5.91f, -5.69f}, { 7.09f, 2.72f}, { 7.78f, -4.06f}, {-0.79f, -7.21f}, {-3.15f, -4.08f}, {-1.89f, 3.27f}, { 4.57f, -2.07f}, {-3.88f, -3.30f}, {-4.89f, 4.20f}, { 4.10f, -6.70f}, { 3.28f, -3.84f}, { 3.84f, 1.19f} }; /* Executable statements */ printf( "LAPACKE_cgesvd (row-major, high-level) Example Program Results\n" ); /* Compute SVD */ info = LAPACKE_cgesvd( LAPACK_ROW_MAJOR, 'A', 'A', m, n, a, lda, s, u, ldu, vt, ldvt, superb ); /* Check for convergence */ if( info > 0 ) { printf( "The algorithm computing SVD failed to converge.\n" ); exit( 1 ); } /* Print singular values */ print_rmatrix( "Singular values", 1, m, s, 1 ); /* Print left singular vectors */ print_matrix( "Left singular vectors (stored columnwise)", m, m, u, ldu ); /* Print right singular vectors */ print_matrix( "Right singular vectors (stored rowwise)", m, n, vt, ldvt ); exit( 0 ); } /* End of LAPACKE_cgesvd Example */ /* Auxiliary routine: printing a matrix */ void print_matrix( char* desc, MKL_INT m, MKL_INT n, MKL_Complex8* 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,%6.2f)", a[i*lda+j].real, a[i*lda+j].imag ); printf( "\n" ); } } /* Auxiliary routine: printing a real matrix */ void print_rmatrix( 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" ); } }

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