The Architecture and Circuital Implementation Scheme of A New Generalized Cellular Automata
Shuai Dian · Chinese Journal of Computers · 2004
Authors have proposed the conception and parallel algorithm of a generalized cellular automata (GCA) for effectively solving a class of optimization problems in computer networks, such as the Fast Packet Switching problem. This paper further discusses the issues about the architecture,hardware implementation and circuital design scheme of the GCA, which is essential to the applications of GCA approach. Unlike the Hopfield-type neural network (HNN) and cellular neural network (CNN), the proposed GCA has a pyramid architecture that is composed of multi-layer multi-granularity macro-cells, and has the multi-granularity evolution dynamics. In a GCA there is no direct interconnection among the macro-cells with the same granularity, whereas there are some interactions among different macro-cell layers, which not only significantly improves the real-time performance for problem-solving, but also greatly simplifies the hardware structure of GCA. The GCA architecture and its circuital implementation scheme have advantages over the HNN and CNN methods in terms of the real-time performance, interconnection complexity, and parameter selection.