Processor allocation for a class of hypercube-like supercomputers

Modified hypercubes (MHs) have been proposed as the building blocks of hypercube-based parallel systems that support incremental growth techniques. In contrast, systems comprising the standard hypercube cannot be expanded in practice. Processor allocation for MHs is a more difficult task due to a slight deviation in their topology from that of the hypercube. The authors address the processor allocation problem for MHs and propose two strategies which are based, partially or entirely, on a table lookup approach. The proposed strategies are characterized by a perfect subcube recognition ability and a superior performance. Furthermore, two existing processor allocation strategies for pure hypercubes, namely the buddy and free list strategies, are shown to be ineffective for MHs, in the light of their inability to recognize many available subcubes