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The computations involved with each element in the array is independent from the rest of the elements, and therefore this function is a deserving candidate for parallelization. Additionally, the array elements can be evenly distributed into sub-arrays and a process can be assigned to each sub-array.
=== Assignment 2 & 3 ===
For Assignment 2, we decided to parallelize the application selected by Bruno.
In the code, the function that took up a significant amount of time was the calculateDimensions() function. The flat profile indicates that this function takes 97.67% of the execution time.
[[File:TimeComparison.PNG]]
=== Assignment 3 ===
To optimize our code, we used shared memory inside the kernel. This reduced the run time for each problem size
