Abstract
Gang scheduling is currently the most popular scheduling scheme for parallel processing in a time shared environment. In this paper we .rst describe the ideas of job re-packing and workload tree for e.ciently allocating resources to enhance the performance of gang scheduling. We then present some experimental results obtained by implementing four di.erent resource allocation schemes. These results show how the ideas, such as re-packing jobs, running jobs in multiple slots and minimising the average number of time slots in the system, a.ect system and job performance when incorporated into the buddy based allocation scheme for gang scheduling.KeywordsTime SlotAllocation SchemeResource Allocation SchemeIdle SlotWorkload ConditionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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