Design and Implementation of Reconfigurable Neuro-Inspired Computing Model on a FPGA

Abstract

In this paper we design a large scale reconfigurable digital bio-inspired computing model. We consider the reconfigurable and event driven parameters in the developed fieldprogrammable neuromorphic computing system. The various Intellectual Property (IP) cores are developed for the modules such as Block RAM, Differential Clock, Floating Point, and First In First Out (FIFO) for the design of the neuron model in Xilinx ISE, with exploration of register transfer logic (RTL) and hardware synthesis using Verilog code. The architecture for design at device level offers the best possible design tradeoff for specific processor architectures and development choices. In this paper we perform algorithmic design of a large scale reconfigurable logical bio-inspired computing model. The proposed algorithm is implemented on Field Programmable Gate Array (FPGA) to develop a neuron model to be utilized in neuromorphic computing system.