Architecture design of re-configurable convolutional neural network on software definition

Abstract

In order to meet the flexibility and efficiency requirement in convolutional neural network (CNN), an architecture of re-configurable CNN based on software definition was proposed. In the architecture, the process of CNN could be normalized and the operation mode could be accelerated. The calculation pipeline was implemented by using dual bus architecture based on AHB and AXI protocols. By software definition, the proposed architecture, which could realize the real-time processing of data among different CNN structure, was implemented on FPGA. The result shows that at least 2 CNN models can be software defined on the FPGA circuit. The output measures an operation processing capacity of 10 times that of CPU, and an operation energy consumption ratio of 2 times that of GPU.

Keywords

• convolutional neural network
• software definition
• dynamic reconfiguration
• fpga
• pipeline calculation
• soc