Design and Implementation of Convolutional Neural Network Based on FPGA

Convolutional neural networks (CNN) have achieved great success in various computer vision applications.The parallel architecture of convolutional neural networks were studied in this paper.Based on the parallel characteristics of network computing, a parallel CNN forward propagation architecture was proposed.The experimental results showed that under the operating frequency of 110MHz, the architecture could make the FPGA peak operating speed of 0.48GOP/s, compared to the ARM Mali-T628GPU platform to achieve 23.5×speed.