IJCNS

COMPARATIVE ANALYSIS OF PVM AND MPI FOR THE DEVELOPMENT OF PHYSICAL APPLICATIONS IN PARALLEL AND DISTRIBUTED SYSTEMS

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Abstract

This research is aimed to explore each of these two Parallel Virtual Machine (PVM) and Message Passing Interface(MPI) vehicles for DPP (Distributed Parallel Processing) considering capability, ease of use, and availability, and compares their distinguishing features and also explores programmer interface and their utilization for solving real world parallel processing applications. This work recommends a potential research issue, that is, to study the feasibility of creating a programming environment that allows access to the virtual machine features of PVM and the message passing features of MPI. PVM and MPI, two systems for programming clusters, are often compared. Each system has its unique strengths and this will remain so in to the foreseeable future. The comparisons usually start with the unspoken assumption that PVM and MPI represent different solutions to the same problem. In this paper we show that, in fact, the two systems often are solving different problems. In cases where the problems do match but the solutions chosen by PVM and MPI are different, we explain the reasons for the differences. Usually such differences can be traced to explicit differences in the goals of the two systems, their origins, or the relationship between their specifications and their implementations. This paper also compares PVM and MPI features, pointing out the situations where one may be favored over the other; it explains the deference’s between these systems and the reasons for such deference’s.

Recommended Citation

[1] W. Gropp and E. Lusk. Goals Guiding Design: PVM and MPI. [2] I. Foster. Designing and building parallel programs. Addison-Wesley, 1995. ISBN 0-201- 57594-9, http://www.mcs.anl.gov/dbpp. [3] G. A. Geist, J. A. Kohl, and P. M. Papadopoulos. PVM and MPI: A comparison of features. Calculateurs Paralleles, 8(2), 1996. [4] G. E. Fagg, A. Bukovsky, and J. J. Dongarra. HARNESS and fault tolerant MPI. Parallel Computing, 27(11):1479– 1495, Oct. 2001.