Abstract
Parallel sorting algorithms order a set of elements USING MULTIPLE processors in order to enhance the performance of sequential sorting algorithms. In general, the performance of sorting algorithms are EVALUATED IN term of algorithm growth rate according to the input size. In this paper, the running time, parallel speedup and parallel efficiency OF PARALLEL bubble sort is evaluated and measured. Message Passing Interface (MPI) IS USED for implementing the parallel version of bubble sort and IMAN1 supercomputer is used to conduct the results. The evaluation results show that parallel bubble sort has better running time as the number of processors increases. On other hand, regarding parallel efficiency, parallel bubble sort algorithm is more efficient to be applied OVER SMALL number of processors
Highlights
Element sorting is one of the most fundamental process for many algorithms such as searching and load balancing
The Objective of this paper is to evaluate the performance of parallel bubble sort
Many performance metrics are used for evaluating parallel bubble sort including the running time, speedup, parallel efficiency, communication cost, and parallel granularity according to a different number of processors
Summary
Element sorting is one of the most fundamental process for many algorithms such as searching and load balancing. Sequential sorting algorithms vary in their time complexity. In order to enhance the performance of sequential sorting algorithms, parallel versions have been implemented. These parallel algorithms aim to reduce the overall execution time and increase the fault-tolerance of sorting based applications [2n]. The Objective of this paper is to evaluate the performance of parallel bubble sort. Many performance metrics are used for evaluating parallel bubble sort including the running time, speedup, parallel efficiency, communication cost, and parallel granularity according to a different number of processors.
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