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  • 12/20/2021
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LAPACKE_sgesvd Example Program in C for Column 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_sgesvd Example. ======================= Program computes the singular value decomposition of a general rectangular matrix A: 8.79 9.93 9.83 5.45 3.16 6.11 6.91 5.04 -0.27 7.98 -9.15 -7.93 4.86 4.85 3.01 9.57 1.64 8.83 0.74 5.80 -3.49 4.02 9.80 10.00 4.27 9.84 0.15 -8.99 -6.02 -5.31 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. 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_sgesvd (column-major, high-level) Example Program Results Singular values 27.47 22.64 8.56 5.99 2.01 Left singular vectors (stored columnwise) -0.59 0.26 0.36 0.31 0.23 -0.40 0.24 -0.22 -0.75 -0.36 -0.03 -0.60 -0.45 0.23 -0.31 -0.43 0.24 -0.69 0.33 0.16 -0.47 -0.35 0.39 0.16 -0.52 0.29 0.58 -0.02 0.38 -0.65 Right singular vectors (stored rowwise) -0.25 -0.40 -0.69 -0.37 -0.41 0.81 0.36 -0.25 -0.37 -0.10 -0.26 0.70 -0.22 0.39 -0.49 0.40 -0.45 0.25 0.43 -0.62 -0.22 0.14 0.59 -0.63 -0.44 */ #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, float* a, MKL_INT lda ); /* Parameters */ #define M 6 #define N 5 #define LDA M #define LDU M #define LDVT N /* Main program */ int main() { /* Locals */ MKL_INT m = M, n = N, lda = LDA, ldu = LDU, ldvt = LDVT, info; float superb[min(M,N)-1]; /* Local arrays */ float s[N], u[LDU*M], vt[LDVT*N]; float a[LDA*N] = { 8.79f, 6.11f, -9.15f, 9.57f, -3.49f, 9.84f, 9.93f, 6.91f, -7.93f, 1.64f, 4.02f, 0.15f, 9.83f, 5.04f, 4.86f, 8.83f, 9.80f, -8.99f, 5.45f, -0.27f, 4.85f, 0.74f, 10.00f, -6.02f, 3.16f, 7.98f, 3.01f, 5.80f, 4.27f, -5.31f }; /* Executable statements */ printf( "LAPACKE_sgesvd (column-major, high-level) Example Program Results\n" ); /* Compute SVD */ info = LAPACKE_sgesvd( LAPACK_COL_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_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_sgesvd 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+j*lda] ); printf( "\n" ); } }

Product and Performance Information

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Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.