Parallelize write_transformation funcs

src/main.cpp

@@ -4,7 +4,7 @@
  *  The program performs the Jacobi rotation method. 
  *  The size of the matrix, and number of transformations
  *  performed are written to file. 
- *  Eigenvector correstonding to the 3 smallest eigenvalues 
+ *  Eigenvector corresponding to the 3 smallest eigenvalues 
  *  for matrices of size 6x6 and 100x100 are written to file.
  *
  *  @author Cory Alexander Balaton (coryab)
@@ -13,7 +13,10 @@
  */
 #include <cassert>
 #include <cmath>
+#include <ctime>
 #include <iostream>
+#include <omp.h>
+#include <ostream>
 
 #include "utils.hpp"
 #include "matrix.hpp"
@@ -28,6 +31,7 @@ void write_transformation_dense(int N)
     ofile << "N,T" << std::endl;
 
     // Increase size of matrix, start at 5 to avoid logic_error of N=4
+    #pragma omp parallel for ordered schedule(static, 1)
     for (int i = 5; i <= N; i++) {
         arma::mat A = arma::mat(i, i).randn();
         A = arma::symmatu(A);
@@ -40,8 +44,11 @@ void write_transformation_dense(int N)
         jacobi_eigensolver(A, 10e-14, eigval, eigvec, 100000, iters, converged);
 
         // Write size, and number of iterations to file
+        #pragma omp ordered
+        {
             ofile << i << "," << iters << std::endl;
         }
+    }
     ofile.close();
 }
 
@@ -58,6 +65,7 @@ void write_transformation_tridiag(int N)
     ofile << "N,T" << std::endl;
 
     // Increase size of matrix, start at 5 to avoid logic_error of N=4
+    #pragma omp parallel for ordered schedule(static, 1)
     for (int i = 5; i <= N; i++) {
         h = 1. / (double) (i+1);
         a = -1. / (h*h), d = 2. / (h*h);
@@ -72,8 +80,11 @@ void write_transformation_tridiag(int N)
         jacobi_eigensolver(A, 10e-14, eigval, eigvec, 100000, iters, converged);
 
         // Write size, and number of iterations to file
+        #pragma omp ordered
+        {
             ofile << i << "," << iters << std::endl;
         }
+    }
     ofile.close();
 }