Table of Contents

Contents Number Test Software Manual

Name: Condition Number Test

Author: Philip Nelson

Language: C++. The code can be compiled using the GNU C++ compiler (gcc). A make file is included to compile an example program

For example,

make

will produce an executable ./conditionTest.out that can be executed.

Description/Purpose: The purpose of this code is to test the performance of the parallel vs serial algorithm to compute the condition number of a matrix, A.

Usage/Example:

int main()
{
  auto A = generate_square_symmetric_diagonally_dominant_matrix(50u);

  auto start = std::chrono::high_resolution_clock::now();
  auto conditionNum1 = condition_2_estimate(A, 100u);
  auto end = std::chrono::high_resolution_clock::now();
  auto result1 = std::chrono::duration<double, std::milli>(end - start).count();

  start = std::chrono::high_resolution_clock::now();
  auto conditionNum2 = parallel_condition_2_estimate(A, 100u);
  end = std::chrono::high_resolution_clock::now();
  auto result2 = std::chrono::duration<double, std::milli>(end - start).count();

  std::cout << "serial algorithm:\n  result: " << conditionNum1
            << "\n  time: " << result1 << std::endl
            << std::endl;

  std::cout << "parallel algorithm:\n  result: " << conditionNum2
            << "\n  time: " << result2 << std::endl
            << std::endl;
}

Output from the lines above

serial algorithm:
  result: 74.3532
  time: 945.851

parallel algorithm:
  result: 74.3532
  time: 931.078

explanation of output:

The results were not greatly in favor of the parallel algorithm. Both algorithms performed similarly with the parallel version outperforming the serial version by a small margin. In the output from above, the parallel version was only 1.4% faster.

Last Modified: December 2018