Generative AI On A General-Purpose Neural Processor (GPNPU)

Generative-AI workloads evolve on a quarterly cadence, with novel attention variants, quantization formats, and routing schemes appearing faster than fixed-function neural-processor silicon can be respun. This paper presents the General-Purpose Neural Processor (GPNPU): a single programmable processor architecture, delivered as configurable IP, that unifies scalar, vector, and matrix execution in one instruction-set architecture (ISA) and one programming model accessible from standard C++ and Py