A fast recognition-complete processor allocation strategy for hypercube computers

Fully recognizing various subcubes in a hypercube computer efficiently is addressed. A method with much less complexity than the multiple-GC strategy in generating the search space, while achieving complete subcube recognition, is proposed. This method is referred to as a dynamic processor allocation scheme because the search space generated is dependent on the dimension of the requested subcube dynamically. The basic idea lies in collapsing the binary tree representations of a hypercube successively so that the nodes which form a subcube but are distant are brought close to each other for recognition. The strategy can be implemented efficiently by using right rotating operations on the notations of the sets of subcubes corresponding to the nodes at a certain level of binary tree representations. Results of extensive simulation runs carried out to collect performance measures for different allocation strategies are discussed. It is shown that this strategy compares favorably in most situations with other known allocation schemes capable of achieving complete subcube recognition