Parallel Processing Capacity
of Privately Owned Networks of Workstations

Linguo Gong,
Xian-He Sun*,
Edward F. Watson

Department of Information Systems and Decision Sciences
Department of Computer Science*
Louisiana State University
Baton Rouge, LA 70803-4020

Technical Reprot #97-16

Department of Computer Science
Louisiana State University
Baton Rouge, LA 70803-4020


The low cost and wide availability of networks of workstations have made them an attractive solution for high performance computing. However, while a network of workstations may be readily available, these workstations may be privately owned and the owners may not want to share their computing resources with others. Assuming machine owners have a preemptive priority, in this paper, we study the parallel processing capacity of a privately owned network of workstations. A stochastic model is developed to predict performance of non-dedicated network computing. It considers heterogeneous machine utilization and heterogeneous service distribution, and it uniquely separates the influence of machine utilization, sequential job service rate, and parallel task allocation on the parallel completion. In addition, this model is general, simple and easy to use. It is designed to provide a practical guideline for task scheduling in a non-dedicated environment.