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/*
* Copyright (C) 2023-2025 Colin Ian King
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
*
*/
extern "C" {
#include "config.h"
#include "stress-eigen-ops.h"
extern double stress_time_now(void);
}
#if defined(HAVE_EIGEN)
#define THRESHOLD (0.0001)
#include <eigen3/Eigen/Dense>
using namespace Eigen;
template <typename T> static int eigen_add(const size_t size, double *duration, double *count)
{
try {
typedef Matrix < T, Dynamic, Dynamic > matrix;
matrix a, b, result, result_check;
double t;
bool r;
a = matrix::Random(size, size);
b = matrix::Random(size, size);
t = stress_time_now();
result = a + b;
*duration += stress_time_now() - t;
*count += 1.0;
t = stress_time_now();
result_check = a + b;
*duration += stress_time_now() - t;
*count += 1.0;
r = ((result_check - result).norm() < THRESHOLD);
if (!r)
return EXIT_FAILURE;
} catch (...) {
return -1;
}
return EXIT_SUCCESS;
}
template <typename T> static int eigen_multiply(const size_t size, double *duration, double *count)
{
try {
typedef Matrix < T, Dynamic, Dynamic > matrix;
matrix a, b, result, result_check;
double t;
bool r;
a = matrix::Random(size, size);
b = matrix::Random(size, size);
t = stress_time_now();
result = a * b;
*duration += stress_time_now() - t;
*count += 1.0;
t = stress_time_now();
result_check = a * b;
*duration += stress_time_now() - t;
*count += 1.0;
r = ((result_check - result).norm() < THRESHOLD);
if (!r)
return EXIT_FAILURE;
} catch (...) {
return -1;
}
return EXIT_SUCCESS;
}
template <typename T> static int eigen_transpose(const size_t size, double *duration, double *count)
{
try {
typedef Matrix < T, Dynamic, Dynamic > matrix;
matrix a, result, result_check;
double t;
bool r;
a = matrix::Random(size, size);
t = stress_time_now();
result = a.transpose();
*duration += stress_time_now() - t;
*count += 1.0;
t = stress_time_now();
result_check = a.transpose();
*duration += stress_time_now() - t;
*count += 1.0;
r = ((result_check - result).norm() < THRESHOLD);
if (!r)
return EXIT_FAILURE;
} catch (...) {
return -1;
}
return EXIT_SUCCESS;
}
template <typename T> static int eigen_inverse(const size_t size, double *duration, double *count)
{
try {
typedef Matrix < T, Dynamic, Dynamic > matrix;
matrix a, result, result_check;
double t;
bool r;
a = matrix::Random(size, size);
t = stress_time_now();
result = a.inverse();
*duration += stress_time_now() - t;
*count += 1.0;
t = stress_time_now();
result_check = a.inverse();
*duration += stress_time_now() - t;
*count += 1.0;
r = ((result_check - result).norm() < THRESHOLD);
if (!r)
return EXIT_FAILURE;
} catch (...) {
return -1;
}
return EXIT_SUCCESS;
}
template <typename T> static int eigen_determinant(const size_t size, double *duration, double *count)
{
try {
typedef Matrix < T, Dynamic, Dynamic > matrix;
matrix a;
T result, result_check;
double t;
a = matrix::Random(size, size);
t = stress_time_now();
result = a.determinant();
*duration += stress_time_now() - t;
*count += 1.0;
t = stress_time_now();
result_check = a.determinant();
*duration += stress_time_now() - t;
*count += 1.0;
if ((result_check - result) > 0.0001)
return EXIT_FAILURE;
} catch (...) {
return -1;
}
return EXIT_SUCCESS;
}
extern "C" {
int eigen_add_long_double(const size_t size, double *duration, double *count)
{
return eigen_add<long double>(size, duration, count);
}
int eigen_add_double(const size_t size, double *duration, double *count)
{
return eigen_add<double>(size, duration, count);
}
int eigen_add_float(const size_t size, double *duration, double *count)
{
return eigen_add<float>(size, duration, count);
}
int eigen_multiply_long_double(const size_t size, double *duration, double *count)
{
return eigen_multiply<long double>(size, duration, count);
}
int eigen_multiply_double(const size_t size, double *duration, double *count)
{
return eigen_multiply<double>(size, duration, count);
}
int eigen_multiply_float(const size_t size, double *duration, double *count)
{
return eigen_multiply<float>(size, duration, count);
}
int eigen_transpose_long_double(const size_t size, double *duration, double *count)
{
return eigen_transpose<long double>(size, duration, count);
}
int eigen_transpose_double(const size_t size, double *duration, double *count)
{
return eigen_transpose<double>(size, duration, count);
}
int eigen_transpose_float(const size_t size, double *duration, double *count)
{
return eigen_transpose<float>(size, duration, count);
}
int eigen_inverse_long_double(const size_t size, double *duration, double *count)
{
return eigen_inverse<long double>(size, duration, count);
}
int eigen_inverse_double(const size_t size, double *duration, double *count)
{
return eigen_inverse<double>(size, duration, count);
}
int eigen_inverse_float(const size_t size, double *duration, double *count)
{
return eigen_inverse<float>(size, duration, count);
}
int eigen_determinant_long_double(const size_t size, double *duration, double *count)
{
return eigen_determinant<long double>(size, duration, count);
}
int eigen_determinant_double(const size_t size, double *duration, double *count)
{
return eigen_determinant<double>(size, duration, count);
}
int eigen_determinant_float(const size_t size, double *duration, double *count)
{
return eigen_determinant<float>(size, duration, count);
}
}
#endif
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