PROCESSOR SAVING SCHEDULING POLICIES FOR MULTIPROCESSOR SYSTEMS

Abstract

Various techniques for multiprogramming parallel multiprocessors systems have been proposed as a way to improve performance. A natural approach is to divide the set of processing elements into independent partitions, and simultaneously execute a different parallel program in each partition. Several issues arise, including the determination of the optimal number of programs allowed to execute simultaneously (i.e., the number of partitions) and the corresponding partition sizes. This can be done statically, dynamically, or adaptively, depending on the system and workload characteristics. In this dissertation, processor scheduling policies that "save" processors have been discussed and implemented. In a multiprogrammed parallel system, a "processor-saving-adaptive" scheduling policy purposefully keeps some of the available processors idle in the presence of work to be done. The condition under which processor saving policies, can be more effective than their greedy counterparts, i.e., policies that never leave processors idle in the presence of work to be done , are examined. Sensitive analysis is performed with respect to application . speedup; coefficient of variation of the application execution time, variability in the arrival process, and multiclass workloads. Simulation results show . that processor saving policies outperform their greedy counterparts.