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Intel® oneAPI Math Kernel Library LAPACK Examples

ID 766877
Date 3/31/2023
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LAPACKE_cheevd Example Program in C for Row Major Data Layout

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/*
   LAPACKE_cheevd Example.
   =======================

   Program computes all eigenvalues and eigenvectors of a complex Hermitian
   matrix A using divide and conquer algorithm, where A is:

   (  3.40,  0.00) ( -2.36, -1.93) ( -4.68,  9.55) (  5.37, -1.23)
   ( -2.36,  1.93) (  6.94,  0.00) (  8.13, -1.47) (  2.07, -5.78)
   ( -4.68, -9.55) (  8.13,  1.47) ( -2.14,  0.00) (  4.68,  7.44)
   (  5.37,  1.23) (  2.07,  5.78) (  4.68, -7.44) ( -7.42,  0.00)

   Description.
   ============

   The routine computes all eigenvalues and, optionally, eigenvectors of an
   n-by-n complex Hermitian matrix A. The eigenvector v(j) of A satisfies

   A*v(j) = lambda(j)*v(j)

   where lambda(j) is its eigenvalue. The computed eigenvectors are
   orthonormal.
   If the eigenvectors are requested, then this routine uses a divide and
   conquer algorithm to compute eigenvalues and eigenvectors.

   Example Program Results.
   ========================

 LAPACKE_cheevd (row-major, high-level) Example Program Results

 Eigenvalues
 -21.97  -0.05   6.46  16.34

 Eigenvectors (stored columnwise)
 (  0.41,  0.00) ( -0.34,  0.00) ( -0.69,  0.00) (  0.49,  0.00)
 (  0.02, -0.30) (  0.32, -0.21) ( -0.57, -0.22) ( -0.59, -0.21)
 (  0.18,  0.57) ( -0.42, -0.32) (  0.06,  0.16) ( -0.35, -0.47)
 ( -0.62, -0.09) ( -0.58,  0.35) ( -0.15, -0.31) ( -0.10, -0.12)
*/
#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, 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 N 4
#define LDA N

/* Main program */
int main() {
        /* Locals */
        MKL_INT n = N, lda = LDA, info;
        /* Local arrays */
        float w[N];
        MKL_Complex8 a[LDA*N] = {
           { 3.40f,  0.00f}, { 0.00f,  0.00f}, { 0.00f,  0.00f}, { 0.00f,  0.00f},
           {-2.36f,  1.93f}, { 6.94f,  0.00f}, { 0.00f,  0.00f}, { 0.00f,  0.00f},
           {-4.68f, -9.55f}, { 8.13f,  1.47f}, {-2.14f,  0.00f}, { 0.00f,  0.00f},
           { 5.37f,  1.23f}, { 2.07f,  5.78f}, { 4.68f, -7.44f}, {-7.42f,  0.00f}
        };
        /* Executable statements */
        printf( "LAPACKE_cheevd (row-major, high-level) Example Program Results\n" );
        /* Solve eigenproblem */
        info = LAPACKE_cheevd( LAPACK_ROW_MAJOR, 'V', 'L', n, a, lda, w );
        /* Check for convergence */
        if( info > 0 ) {
                printf( "The algorithm failed to compute eigenvalues.\n" );
                exit( 1 );
        }
        /* Print eigenvalues */
        print_rmatrix( "Eigenvalues", 1, n, w, 1 );
        /* Print eigenvectors */
        print_matrix( "Eigenvectors (stored columnwise)", n, n, a, lda );
        exit( 0 );
} /* End of LAPACKE_cheevd 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" );
        }
}