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Algorithm Research & Explore
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1079-1083

PipeCNN:parallelization of convolutional neural network based on software pipeline technology

Wu Peng
Zhou Ningning
School of Computer, Nanjing University of Posts & Telecommunications, Nanjing 210023, China

Abstract

Aiming at the traditional model parallel methods for accelerating convolution neural network(CNN) tend to have low utilization, this paper proposed PipeCNN, which accelerated CNN with software pipeline. Firstly, this paper studied the forward propagation and back propagation, and then explored data correlation during training. Secondly, it parallelized CNN with the support of software pipeline, and then analyzed two feasible gradient updating methods in PipeCNN. Finally, it used circular queue to realize communication between two layers and then proposed a task allocation algorithm to divide CNN into working parts. Experiments show that the method can obtain good speedup and utilization while ensuring the accuracy of the model. It shows that software pipeline can effectively solve the problem of low utilization in model parallel, and accelerate the training of CNN.

Foundation Support

智能电网保护和运行控制国家重点实验室开放课题资助项目(201610,20169)
国家自然基金资助项目(61170322,61373065,61302157)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.02.0038
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 4
Section: Algorithm Research & Explore
Pages: 1079-1083
Serial Number: 1001-3695(2021)04-021-1079-05

Publish History

[2021-04-05] Printed Article

Cite This Article

吴鹏, 周宁宁. PipeCNN:一种基于软件流水线的并行化卷积神经网络方法 [J]. 计算机应用研究, 2021, 38 (4): 1079-1083. (Wu Peng, Zhou Ningning. PipeCNN:parallelization of convolutional neural network based on software pipeline technology [J]. Application Research of Computers, 2021, 38 (4): 1079-1083. )

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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.


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