A practical network of workstations is heterogeneous where computing power varies in different composing workstations. A simple loop scheduling technique is insufficient in exploiting maximum computing power of such a system.
We propose a fundamental idea for a performance prediction tool to gauge the relative computing power among composing workstations so that parallel performance of a program run on a given network can be predicted. In view of the performance prediction results, a loop scheduling approach is then incorporated into the system to achieve close-to-optimal parallel performance.
Examples running benchmark programs demonstrate a significant gain from the proposed approach over traditional scheduling approaches.