lapack_int LAPACKE_sgetrf_work( int matrix_layout, lapack_int m, lapack_int n,
float* a, lapack_int lda, lapack_int* ipiv )
{
lapack_int info = 0;
if( matrix_layout == LAPACK_COL_MAJOR ) {
/* Call LAPACK function and adjust info */
LAPACK_sgetrf( &m, &n, a, &lda, ipiv, &info );
if( info < 0 ) {
info = info - 1;
}
} else if( matrix_layout == LAPACK_ROW_MAJOR ) {
lapack_int lda_t = MAX(1,m);
float* a_t = NULL;
/* Check leading dimension(s) */
if( lda < n ) {
info = -5;
LAPACKE_xerbla( "LAPACKE_sgetrf_work", info );
return info;
}
/* Allocate memory for temporary array(s) */
a_t = (float*)LAPACKE_malloc( sizeof(float) * lda_t * MAX(1,n) );
if( a_t == NULL ) {
info = LAPACK_TRANSPOSE_MEMORY_ERROR;
goto exit_level_0;
}
/* Transpose input matrices */
LAPACKE_sge_trans( matrix_layout, m, n, a, lda, a_t, lda_t );
/* Call LAPACK function and adjust info */
LAPACK_sgetrf( &m, &n, a_t, &lda_t, ipiv, &info );
if( info < 0 ) {
info = info - 1;
}
/* Transpose output matrices */
LAPACKE_sge_trans( LAPACK_COL_MAJOR, m, n, a_t, lda_t, a, lda );
/* Release memory and exit */
LAPACKE_free( a_t );
exit_level_0:
if( info == LAPACK_TRANSPOSE_MEMORY_ERROR ) {
LAPACKE_xerbla( "LAPACKE_sgetrf_work", info );
}
} else {
info = -1;
LAPACKE_xerbla( "LAPACKE_sgetrf_work", info );
}
return info;
}
int main (int argc,char* argv[])
{
// Some needed ints. n=size of matrix, info = error checker from ssyev
lapack_int n=5,info;
/* Declare matrix of values! */
float atemp[n*n] = {
1.96f, -6.49f, -0.47f, -7.20f, -0.65f,
0.00f, 3.80f, -6.39f, 1.50f, -6.34f,
0.00f, 0.00f, 4.17f, -1.51f, 2.67f,
0.00f, 0.00f, 0.00f, 5.70f, 1.80f,
0.00f, 0.00f, 0.00f, 0.00f, -7.10f
};
/* Copy to a vector! */
std::vector<float> a(n*n);
/* Declare vector to hold eigenvalues! */
std::vector<float> w(n);
/* Move data to the std::vector a*/
std::memcpy(&a[0],atemp,n*n*sizeof(float));
/* Make a working vector! */
std::vector<float> c(n*n);
std::memcpy(&c[0],&a[0],n*n*sizeof(float));
/* -------------------- Eigenvalues with lapack ----------------- */
/* Example of how to use std::vector with ssyev */
info = LAPACKE_ssyev( LAPACK_ROW_MAJOR,'V','U',n,&c[0],n,&w[0] );
/* Error checking */
if (info > 0)
{
std::cout << "Diagonalization failed! Error code: " << info << std::endl;
exit(EXIT_FAILURE);
}
/* -------------------------------------------------------------- */
/* Print the eigenvalues */
std::cout << "Eigenvalues: " << std::endl;
for (int j=0;j<n;++j)
{
std::cout << w[j] << " ";
}
std::cout << std::endl;
/* Print the eigenvectors */
std::cout << "Eigenvectors: " << std::endl;
for (int i=0;i<n;++i)
{
for (int j=0;j<n;++j)
{
std::cout << c[i*n+j] << " ";
}
std::cout << std::endl;
}
std::memcpy(&c[0],&a[0],n*n*sizeof(float));
/* -------------------- Matrix inverse with Lapack ----------------- */
// Seg faults on my machine, some problem with pthreads, but you get the point
lapack_int ipiv[n];
LAPACK_sgetrf(&n,&n,&c[0],&n,ipiv,&info);
// Error checking
if (info > 0)
{
std::cout << "Inversion failed! Error code: " << info << std::endl;
exit(EXIT_FAILURE);
}
info = LAPACKE_sgetri( n,n,&c[0],n,ipiv );
// Error checking
if (info > 0)
{
std::cout << "Inversion failed! Error code: " << info << std::endl;
exit(EXIT_FAILURE);
}
/* ----------------------------------------------------------------- */
/* -------------------- Matrix Mult with cBlas ----------------- */
std::vector<float> b(n*n);
cblas_sgemm(CblasRowMajor,CblasTrans,CblasNoTrans,n,n,1,1.0f,&a[0],n,&c[0],n,0.0f,&b[0],n);
//cblas_sgemm(CblasRowMajor,CblasNoTrans,CblasNoTrans,n,n,1,1.0f,&c[0],n,&a[0],n,0.0f,&b[0],n);
/* -------------------------------------------------------------- */
/* Print the eigenvectors */
std::cout << "Matrx Mult Result: " << std::endl;
for (int i=0;i<n;++i)
{
for (int j=0;j<n;++j)
{
std::cout << b[i*n+j] << " ";
}
std::cout << std::endl;
}
return 0;
}
