METHODOLOGY TO GENERATE EFFICIENT MODELS AND ARCHITECTURES FOR DEEP LEARNING

A system and method of generating an efficient neural network model architecture and an efficient processor for deep learning in an artificial intelligence (AI) processor are provided. The system and method to create the processor architecture as a companion to the neural network model by composing a plurality of processor architectures to enable architectural exploration. The compilation can be implemented for any arbitrary spatial processor architecture using either ASIC or FPGA devices. The processor architecture can be uniquely defined for a selected ML or AI model without having to update the software compiler.