UHC-a massively parallel and distributed realisation of hierarchical classifier networks

In an earlier work on the design of fine-grain, scalable classifiers for massively parallel computers, the technique of unifying cascaded networks has been demonstrated. This paper further examines the method adopted using a highly parallel processing architecture, entitled Unified Hierarchical Classifiers (UHC), based on the principles of Generalised Regression Neural Networks (GRNN). As with the GRNN it has been shown that the resulting classification network can be implemented efficiently on general-purpose multiprocessor platforms without dedicated hardware for processor interconnections. Adding to this the structural simplicity, and the demonstrable potential for an effective distributed realisation on the Cray T3R, will make UHC an attractive classifier architecture in practical applications