Study of Performance Evaluation of Binary Search on Merge Sorted Array Using Different Strategies

Abstract

Abstract-Search algorithm, is an efficient algorithm, which performs an important task that locates specific data among a collection of data. Often, the difference among search algorithms is the speed, and the key is to use the appropriate algorithm for the data set. Binary search is the best and fastest search algorithm that works on the principle of 'divide and conquer'. However, it needs the data collection to be in sorted form, to work properly. In this paper, we study the efficiency of binary search, in terms of execution time and speed up, by evaluating the performance improvement of the combined search algorithms, which are sorted into three different strategies: sequential, multithread, and parallel using message passing interface. The experimental code is written in 'C language' and applied on an IMAN1 supercomputer system. The experimental results show that the decision variables are generated from the IMAN1 supercomputer system, which is the most efficient. It varied for the three different strategies, which applies binary search algorithm on merge sort. The improvement in performance evaluation gained by using parallel code, greatly depends on the size of data set used, and the number of processors that the speed-up of the parallel codes on 2,4,8,16, 32, 64, 128, and 143 processors is best executed, using between a 50,000 and 500,000 dataset size, respectively. Moreover, on a large number of processors, parallel code achieves the best speed-up to a maximum of 2.72.

High Performance Parallel Sort for Shared and Distributed Memory Mimd

“…First function is for splitting the data recursively till size two elements or less. The second function merges the two sorted lists in one sorted list (Hijazi & Qatawneh 2017). The non-recursive Merge sort.…”

An Approach to Parallel Sorting Using Ternary Search

“…The implementing ternary search require to split the data sequence into three parts. After that data is compared with two mid points based on the comparison data is searched in particular parts [2] In this way searching is done. Time complexity of algorithm is O(log 3 n) in average and worst case.…”

Empirical Analysis Measuring the Performance of Multi-threading in Parallel Merge Sort

“…Moreover, parallel merge sort is frequently used in various domains, including; sorting NoSql databases [8], high-performance computing environments [9], and massively parallel architectures [10,11]. When it comes to executing algorithms in parallel, most studies show results of the performance on several processors [12][13][14][15]. These results will mainly rely on the specifications of the device and the behavior of the execution in terms of multithreading.…”