LACS: A High-Computational-Efficiency Accelerator for CNNs

LACS: A High-Computational-Efficiency Accelerator for CNNs

Convolutional neural networks (CNNs) have become continually deeper. With the increasing depth of CNNs, the invalid calculations caused by padding-zero operations, filling-zero operations and stride length (stride length 1) represent an increasing proportion of all calculations. To adapt to differen...

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Bibliographic Details
Main Authors:	Jiangwei Shang, Lei Qian, Zhan Zhang, Lixing Xue, Hongwei Liu
Format:	Article
Language:	English
Published:	IEEE 2020-01-01
Series:	IEEE Access
Subjects:	Accelerator convolutional neural networks (CNNs) field-programmable gate array (FPGA) buffer mechanism
Online Access:	https://ieeexplore.ieee.org/document/8944026/

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