Journal of Hebei University(Natural Science Edition) >

2019 , Vol. 39 >Issue 1: 99 - 105

DOI: https://doi.org/10.3969/j.issn.1000-1565.2019.01.017

Convolutional neural network acceleration system based on FPGA

  • LI Xiaoyan ,
  • ZHANG Xin ,
  • YAN Xiaobing ,
  • REN Deliang ,
  • LI Yanqing ,
  • FU Changjuan
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  • 1. College of Telecommunications and Information Engineering, Hebei University, Baoding 071002, China; 2. Baoding Yonghong Foundry Machinery Factory, Baoding 072150, China

Received date: 2018-09-02

  Online published: 2019-01-25

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Abstract

In this paper, the convolutional neural network is deployed on the Field Programmable Gate Array(FPGA). As a background, a convolutional neural network is proposed to accelerate hardware. The paper analyzes the structural characteristics of convolutional neural networks, stores, reads, and moves data in a stream-style manner. Next, the convolution unit in each layer of the convolutional neural network is expanded to speed up the multiplication and addition operations. Based on the(FPGA)unique parallel structure, pipeline processing method can effectively improve the efficiency of the operation. From object classification results for the ciafr-10 dataset, at 800MHz operating frequency and without loss of accuracy, FPGA compared to General purpose processor can achieve 4 times speed up, Convolutional neural network through parallel process and multi-stage pipeline process can accelerate forward propagation of convolutional neural networks, being suitable for the demand of practical engineering tasks.

Key words： field programmable gate array(FPGA); convolutional neural network; parallelization; stream-style; classification; accelerate

Cite this article

LI Xiaoyan , ZHANG Xin , YAN Xiaobing , REN Deliang , LI Yanqing , FU Changjuan . Convolutional neural network acceleration system based on FPGA[J]. Journal of Hebei University(Natural Science Edition), 2019 , 39(1) : 99 -105 . DOI: 10.3969/j.issn.1000-1565.2019.01.017

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