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Implementation and Area Optimization of LUT6 Based Convolution Structure on FPGA

Huangtao WU, Wenjin HUANG, Rui CHEN, Yihua HUANG

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Summary :

To implement the parallel acceleration of convolution operation of Convolutional Neural Networks (CNNs) on field programmable gate array (FPGA), large quantities of the logic resources will be consumed, expecially DSP cores. Many previous researches fail to make a well balance between DSP and LUT6. For better resource efficiency, a typical convolution structure is implemented with LUT6s in this paper. Besides, a novel convolution structure is proposed to further reduce the LUT6 resource consumption by modifying the typical convolution structure. The equations to evaluate the LUT6 resource consumptions of both structures are presented and validated. The theoretical evaluation and experimental results show that the novel structure can save 3.5-8% of LUT6s compared with the typical structure.

Publication
IEICE TRANSACTIONS on Fundamentals Vol.E102-A No.12 pp.1813-1815
Publication Date
2019/12/01
Publicized
Online ISSN
1745-1337
DOI
10.1587/transfun.E102.A.1813
Type of Manuscript
Special Section LETTER (Special Section on VLSI Design and CAD Algorithms)
Category

Authors

Huangtao WU
  Sun Yat-sen University
Wenjin HUANG
  Sun Yat-sen University
Rui CHEN
  Sun Yat-sen University
Yihua HUANG
  Sun Yat-sen University

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