The Hamiltonian Path Problem is a classic computer science problem: Given a graph
and two vertices i and j, determine whether there is a path from i to j in the graph that visits
each vertex in the graph exactly once. Now, this problem is well-known to be NP-complete.
I have written a solution to this problem (Hamiltonian_Path.cc) that uses the
next_permutation function in C++ to generate all of the permutations (tours) of the vertices that start at vertex i and end in vertex j. This program will find a Hamiltonian Path, if
it exists. Otheriwse, it will say that no such path exists. However, this program is painfully
slow. On a small graph (small_graph.dat) with 5 vertices, it finds the the tour 2 0 1 3 4
from 2 to 4 in much less than a second. But, on a bigger graph (big.dat) with 13 vertices, it
takes over one minute to find a solution. On bigger graphs (bigger.dat and biggest.dat),
it takes much longer to solve.
For example, on input
5 2 4
0 : 1 2 4
1 : 0 2 3 4
2 : 0 1 3
3 : 1 2 4
4 : 0 1 3
The output of the program should be “Tour = 2 0 1 3 4”.
Your task is to make this code faster using parallel computing.
Modify Hamiltonian_Path.cc using OpenMP so that
1. Your modified program still produces the correct results, and
2. It is at least 75% efficient on bigger.dat on a machine with 4 cores/processors.