Researching | Design and implementation of convolution neural network accelerator for Winograd algorithm based on FPGA

Chinese Journal of Liquid Crystals and Displays, Volume. 38, Issue 11, 1521(2023)

Design and implementation of convolution neural network accelerator for Winograd algorithm based on FPGA

Zhao-xu NIU^1,2 and Hai-jiang SUN^1,2、*

Author Affiliations

¹Changchun Institute of Optics，Fine Mechanics and Physics，Chinese Academy of Sciences，Changchun 130033，China

²University of Chinese Academy of Sciences，Beijing 100049，China

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[1] CHEN H L, HUANG L Z, LIU T R et al. Fourier imager network (FIN): a deep neural network for hologram reconstruction with superior external generalization[J]. Light: Science & Applications, 11, 254(2022).

[2] ZUO C, QIAN J M, FENG S J et al. Deep learning in optical metrology: a review[J]. Light: Science & Applications, 11, 39(2022).

[3] LUO W J, SCHWING A G, URTASUN R. Efficient deep learning for stereo matching[C], 5695-5703(2016).

[4] DENG Z, WANG Y B, LIU L B. Attentive residual dense network of visual attention mechanism for weakly illuminated image enhancement[J]. Chinese Journal of Liquid Crystals and Displays, 36, 1463-1473(2021).

[5] LI X, LI L P, LAZOVIK A et al. RGB-D object recognition algorithm based on improved double stream convolution recursive neural network[J]. Opto-Electronic Engineering, 48, 200069(2021).

[6] ZHOU Q H, WANG Z. A remote sensing target detection algorithm based on multi-scale feature enhancement CNNs[J]. Electronics Optics & Control, 29, 74-81(2022).

[7] LU L Q, ZHENG S Z, XIAO Q C et al. Accelerating convolutional neural networks on FPGAs[J]. Scientia Sinica Informationis, 49, 277-294(2019).

[8] ZHANG J Y, WANG H L, GUO Y et al. Review of deep learning[J]. Application Research of Computers, 35, 1921-1928(2018).

[9] WEI X C, YU C H, ZHANG P et al. Automated systolic array architecture synthesis for high throughput CNN inference on FPGAs[C], 1-6(2017).

[10] LIN X H, YIN S Y, TU F B et al. LCP: A layer clusters paralleling mapping method for accelerating inception and residual networks on FPGA[C], 1-6(2018).

[11] ZHANG C, PRASANNA V. Frequency domain acceleration of convolutional neural networks on CPU-FPGA shared memory system[C](2017).

[12] LAVIN A, GRAY S. Fast algorithms for convolutional neural networks[C], 4013-4021(2016).

[13] LIANG Y, LU L Q, XIAO Q C et al. Evaluating fast algorithms for convolutional neural networks on FPGAs[J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39, 857-870(2020).

[14] HUANG C C, DONG X X, LI Z. Deep pipeline 5×5 convolution method based on two-dimensional Winograd algorithm[J]. Journal of Computer Applications, 41, 2258-2264(2021).

[15] WINOGRAD S[M]. ArithmeticComplexityofComputations, 18-23(1980).

[16] ZHANG C, FANG Z M, ZHOU P P et al. Caffeine: towards uniformed representation and acceleration for deep convolutional neural networks[C](2016).

[17] GUO K Y, SUI L Z, QIU J T et al. Angel-eye: a complete design flow for mapping CNN onto embedded FPGA[J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 37, 35-47(2018).

[18] MEI Z W. Design and FPGA implementation of convolutional neutral network acceleration module[D](2020).

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Zhao-xu NIU, Hai-jiang SUN. Design and implementation of convolution neural network accelerator for Winograd algorithm based on FPGA[J]. Chinese Journal of Liquid Crystals and Displays, 2023, 38(11): 1521

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Paper Information

Category: Research Articles

Received: Jan. 13, 2023

Accepted: --

Published Online: Nov. 29, 2023

The Author Email: Hai-jiang SUN (sunhaijing@126.com)

DOI:10.37188/CJLCD.2023-0013

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