Merge Sort Using Sequential and Parallel Programming

Merge sort is considered to be one of the fastest sorting algorithms. It recursively divides the data set into subarrays until each subarray consists of a single element. The goal of this paper is to analyze the performance of merge sort using sequential and parallel programming. Both algorithms were implemented in Python and were tested for various array sizes. Performance of the sequential and parallel merge sort were evaluated with respect to execution time. The results show that the smaller the number of elements gives good performance when executed by a sequential programming but as the number of elements increases, it is best performed by using parallel programming than sequential.