The processor allocation problem in an n-dimensional hypercube multipro-cessor is similar to the conventional memory allocation problem. The main objective is to maximize the utilization of available resources as well as minimize the inherent system fragmentation. In this thesis, a new processor allocation strategy is proposed, and compared with the existing strategies, such as, the Buddy strategy, the Single Gray Code strategy (SGC), the Multiple Gray Code (MGC), and the Maximal Set of Subcubes (MSS). We will show that our proposed processor allocation strategy outperforms the existing strategies, by having the advantage of being able to allocate unused processors to other jobs/algorithms.
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