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→Sudoku Puzzle Solver by Gurpreet Singh
'''The call graph for the above execution looks like:'''
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Call graph
granularity: each sample hit covers 2 byte(s) no time propagated
[9] checkColumn(int, int) [18] __static_initialization_and_destruction_0(int, int) [8] checkRow(int, int)
[11] checkSquare(int, int, int) [19] __static_initialization_and_destruction_0(int, int) [10] placeNum(int, int)
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From the above Call graph we can see that the program took no time in finding the solution and the maximum number of calls were made to the checkRow, checkColumn and checkSquare function. However, to get a better understanding of the program let's try a harder Sudoku puzzle.
The Call graph for the following looks like:
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Call graph
[6] checkSquare(int, int, int) [20] __static_initialization_and_destruction_0(int, int) [3] placeNum(int, int)
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From the above Call graph we can see that for a harder Sudoku puzzle, the time increased significantly. Moreover, it can also be seen that almost 50% of the time is consumed by the checkRow function, 18.8% by checkColumn and finally 12% by the checkSquare function. Thousand of calls were made to these 3 functions, if we parallelizing these functions then the efficiency of the program can be increased significantly.
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==== Simple Artificial Neural Network by Sukhbeer====
=====Intro=====
The topic I chose is sorting algorithms. I The algorithm that I'll be profiling and analyzing would be a merge sort algorithm written in c++ which can be found [https://codereview.stackexchange.com/questions/128457/recurrent-merge-sort-without-recursion/ Here]. This code would ask the user to input the size of the array and then fill the array with random elements. The size of the array can be extremely large. From the original creator, the size of the array entered was in the tens of thousands. Theoretically, there would be no limit to how much the user can input however the original creator of this code said it would take him the user several hours to sort 10 million elements in the entered array.
