An Empirical Study of Dynamic Load Balancing Strategies for SPMD Application on Cluster of Workstations

摘要

Today, clusters of workstations represent a satisfactory alternative to MPPs and supercomputers in many areas of application. The rapidly reduction of the cost of high performance workstations/PCs makes this technology ever more available. Moreover, new concepts for the integration of individual workstations through Local Area Networks are emerging. High-speed interconnection networks and optimized protocol system architectures are the most important objectives of current research in this field of study. In this paper we focused on the performance of different algorithms on SPMD model based on their controlling parameters. For implementation, a network of workstations has been chosen and PVM libraries have been used. Matrix multiplication has been chosen as the applications. Mainly three algorithms have been studied. Those are fixed granularity; variable granularity (guided self scheduling) and another one global centralized task migration algorithm have been studied.