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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 12
3671-3676,3680

3D-ACC：convolution neural network accelerator based on 3D integrated circuits

Wang Jijun
Hao Ziyu
Li Hongliang
Jiangnan Institute of Computing Technology, Wuxi Jiangsu 214083, China
DOI: 10.19734/j.issn.1001-3695.2019.08.0558

Abstract

In the deep submicron process, increasing chip's integrated scale to improve performance will lead to the decrease of the chip frequency, the sharp increase of power consumption and the decrease of the computational efficiency. Therefore, by using the new technology of 3D integrated circuit, this paper proposed and quantitatively studied a convolution neural network accelerator named 3D-ACC that mapped 2D systolic array onto 3D integrated circuit. Firstly, aiming at 3D-ACC, this paper designed an efficient convolutional mapping algorithm and built its performance model based on related design parameters. Then this paper analyzed the effects of different design parameters on the performance and efficiency of 3D-ACC. The experimental results show that the peak performance of 3D-ACC can achieve up to 32 TFLOPS when adopt the stack structure of 4-layer with 64×64 systolic array, and the actual computational efficiency of 3D-ACC can reach 47.4%, 37.9% and 40.9% when tested with VGG-16, ResNet-50 and Inception V3 model respectively. The computational efficiency of 3D-ACC is obviously superior to a 2D-ACC with the same amount of PEs, the actual computational performance is 1.51×, 1.69× and 1.61× than that of the latter. This paper explores some advantages of 3D integrated circuit in neural network accelerator design, which can be a reference for further improving the performance of neural network accelerator in the future.

Foundation Support

国家“核高基”专项基金资助项目(2018ZX01028-102)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.08.0558
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 12
Section: System Development & Application
Pages: 3671-3676,3680
Serial Number: 1001-3695(2020)12-030-3671-06

Publish History

[2020-12-05] Printed Article

Cite This Article

王吉军, 郝子宇, 李宏亮. 3D-ACC：基于3D集成电路的卷积神经网络加速结构研究 [J]. 计算机应用研究, 2020, 37 (12): 3671-3676,3680. (Wang Jijun, Hao Ziyu, Li Hongliang. 3D-ACC：convolution neural network accelerator based on 3D integrated circuits [J]. Application Research of Computers, 2020, 37 (12): 3671-3676,3680. )

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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