A study on optimal task decomposition of networked parallel computing using PVM |
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Authors: | Kwanjae Seong Han-Gyoo Kim |
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Affiliation: | (1) Department of Mechanical Engineering, Dong-Guk University, 100-715 Seoul, Korea;(2) Department of Computer Engineering, Hong-Ik University, 121-791 Seoul, Korea |
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Abstract: | A numerical study is performed to investigate the effect of task decomposition on networked parallel processes using Parallel
Virtual Machine (PVM), In our study, a PVM program distributed over a network of workstations is used in solving a finite
difference version of a one dimensional heat equation, where natural choice of PVM programming structure would be the master-slave
paradigm with the aim of finding an optimal configuration resulting in least computing time including communication overhead
among machines. Given a set of PVM tasks comprised of one master and five slave programs, it is found that there exists a
pseudo optimal number of machines, which does not necessarily coincide with the number of tasks, that yields the best performance
when the network is under a light usage. Increasing the number of machines beyond this optimal one does not improve computing
performance since increase in communication overhead among the excess number of machines offsets the decrease in CPU time
obtained by distributing the PVM tasks among these machines. However, when the network traffic is heavy, the results exhibit
a more random characteristic that is explained by the random nature of data transfer time. |
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Keywords: | Communication Overhead Heat Equation Networked Parallel Computing Network Traffic Optimal Task Decomposition PVM |
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