The Snap-1 Parallel Ai Prototype

Semantic Network Array Processor (SNAP) is a parallel architecture for knowledge representation and reasoning using the marker-propagation paradigm. The primary application areas of SNAP are Natural Language Understanding and Speech Processing. A first-generation SNAP-1 system has been designed and constructed using an array of 144 Digital Signal Processors organized as 32 multiprocessing clusters with dedicated communication units, a tiered synchronization scheme, and multiported memory network. Issues in the design, performance and scalability of a marker-propagation architecture are addressed. © 1993 IEE