Parallel processing and hardware support of symbols
Masa-aki Fukase, Tomonori Nakamura · 2002
Though indispensible for artificial intelligence (AI), symbols have not always been processed at a satisfactorily high speed by tools from AI. The authors introduce a new scheme and its hardware support for the parallel processing of symbols, using a functional language similar to Lisp. The structure of programs and data in this language is stored as lists with binary-tree links. The parallel processing is composed of the static analysis and dynamic synthesis of this structure. Both processes are supported by a multiple processing element (MPE) system arranged in a rectangular-lattice network topology. MPE is superpipelined in the static analysis to transform the structure and is controlled in a parallel-superpipeline fashion in the dynamic synthesis to evaluate the transformed structure. The symbolic processing by MPE needs less time and memory than usual processing methods. Hence, the scheme is an effective way to organize a powerful AI machine.