RSS 134. zad

#include <omp.h>
#include <iostream>
#include <stdlib.h>
#include <time.h>
#include <iomanip>
using namespace std;

void matrixPrint(double **matrix, int rows, int columns);
double** newRandomMatrix(int rows, int columns, double low, double high);
double** newMatrix(int rows, int columns);

int main(int argc, char *argv[])
{
    int i, j, k;
    int dim = 5;
    omp_set_num_threads(4);

    double **matrix1 = newMatrix(dim, dim);
    double **matrix2 = newMatrix(dim, dim);

    for(i = 0; i < dim; i++) {
        for(j = 0; j < dim; j++) {
            matrix1[i][j] = i + 3;
            matrix2[i][j] = i + 2;
        }
    }
    double **matrix3 = newMatrix(dim, dim);

    #pragma omp parallel for private(i,j,k)
    for (i = 0; i < dim; i++)
    {
        for (j = 0; j < dim; j++)
        {
            for (k = 0; k < dim; k++)
            {
                matrix3[i][j] += matrix1[i][k] * matrix2[k][j];
            }
        }
    }

    cout << "Matrica 1:" << endl;
    matrixPrint(matrix1, dim, dim);
    cout << "Matrica 2:" << endl;
    matrixPrint(matrix2, dim, dim);
    cout << "Matrica 3:" << endl;
    matrixPrint(matrix3, dim, dim);
    return 0;
}

void matrixPrint(double **matrix, int rows, int columns) {
  int i, j;
  std::cout << std::setprecision(2) << std::fixed;
  std::cout << "Matrix: " << rows << "x" << columns << std::endl;
  if (matrix == NULL)
    std::cout << "Matrix is NULL!";
  else {
    for (i = 0; i < rows; i++) {
      for (j = 0; j < columns; j++) {
        std::cout << matrix[i][j] << "\t";
      }
      std::cout << std::endl;
    }
  }
  std::cout << std::endl;
}

double** newMatrix(int rows, int columns) {
  int i, j;
  double **matrix = new double*[rows];

  for(i = 0;i < rows; i++)
  {
    matrix[i] = new double[columns];
    for(j = 0; j < columns; j++)
    {
        matrix[i][j] = 0;
    }
  }

  return matrix;
}

double** newRandomMatrix(int rows, int columns, double low, double high) {
  double **data;
  int i, j;
  data = newMatrix(rows, columns);
  for (i = 0; i < rows; i++) {
    for (j = 0; j < columns; j++) {
      data[i][j] = (high - low)*((double)rand()/RAND_MAX) + low;
    }
  }
  return data;
}