Abstract

Quicksort is well-know algorithm used for sorting, making O(n log n) comparisons to sort a dataset of n items. Being a divide-and-conquer algorithm, it is easily modified to use parallel computing. The aim of this paper is to evaluate the performance of parallel quicksort algorithm and compare it with theoretical performance analysis. To achieve this we implement a tool to do both sequential and parallel quicksort on randomly generated arrays of different size in several runs to provide us with enough data to draw conclusions about the efficiency of using the capability of modern multicore processors together with algorithms designed to increase the speed of sorting large arrays.