Empirical Performance Analysis of Parallel Programs on Wired and Wireless Local Area Networks Using Beowulf Clusters

Abstract

The basic idea about parallel computing is about putting independent processing units together to collectively solve a task. However, the amount of speedup attained by this collection of processing units is a function of several factors, one of which is the interconnection network. This paper focuses on measuring performance of parallel programs deployed on wired and wireless networks. Our experiments were conducted on Beowulf clusters; a parallel computer built using a collection of everyday personal computers. This paper shows empirically that distributed memory parallel programs (MPI) written for Beowulf clusters on wireless LAN (IEEE 802.11 g) do not gain appreciable speedup as the number of processing nodes increases compared to the same parallel programs written for the same Beowulf clusters but on wired LAN. It further shows the impact the kind of network has in the overall performances of parallel programs when a multiprogramming approach is used to achieve speedup.