Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 3
779-783

Research of binary neural network acceleration method based on ARM+FPGA platform

Sun Xiaohui1
Song Qingzeng1
Jin Guanghao1
Jiang Wenchao2
1. School of Computer Science & Technology, Tiangong University, Tianjin 300387, China
2. School of Computers, Guangdong University of Technology, Guangzhou 510006, China
DOI: 10.19734/j.issn.1001-3695.2018.08.0614

Abstract

The existing convolutional neural network(CNN) has complicated structure and bases on huge dataset, so it is difficult to meet the requirement of computing performance and limitation of energy consumption in some practical applications or computing platforms. Aiming at these applications or platforms, this paper studied the binary algorithm based on ARM+FPGA platform and designed a binary neural network(BNN). It reduced the demand for data storage units and simplified the computational complexity. When implemented in the ARM+FPGA platform, it converted the convolution multiply-accumulate operation into XNOR logic and popcount operation, which improved the overall operation efficiency and declined the consumption of energy and resources. At the same time, based on the characteristics of data storage in BNN, this paper proposed a new row-processing algorithm to improve the throughput of the network. In a word, this implementation is superior to the existing FPGA neural network acceleration methods in terms of GOPS, energy and resource efficiency.

Foundation Support

国家自然科学基金资助项目(61702366,61602342,61602344,51607122)
广东省科技计划项目(2017B010124001,2017B090901005)
天津市自然科学基金资助项目(16JCYBJC42300,17JCQNJC04500)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.08.0614
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 3
Section: Algorithm Research & Explore
Pages: 779-783
Serial Number: 1001-3695(2020)03-030-0779-05

Publish History

[2020-03-05] Printed Article

Cite This Article

孙孝辉, 宋庆增, 金光浩, 等. 基于ARM+FPGA平台的二值神经网络加速方法研究 [J]. 计算机应用研究, 2020, 37 (3): 779-783. (Sun Xiaohui, Song Qingzeng, Jin Guanghao, et al. Research of binary neural network acceleration method based on ARM+FPGA platform [J]. Application Research of Computers, 2020, 37 (3): 779-783. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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