Accelerating Deep Neural Networks by Combining Block-Circulant Matrices and Low-Precision Weights

Accelerating Deep Neural Networks by Combining Block-Circulant Matrices and Low-Precision Weights

As a key ingredient of deep neural networks (DNNs), fully-connected (FC) layers are widely used in various artificial intelligence applications. However, there are many parameters in FC layers, so the efficient process of FC layers is restricted by memory bandwidth. In this paper, we propose a compr...

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Bibliographic Details
Main Authors: Zidi Qin, Di Zhu, Xingwei Zhu, Xuan Chen, Yinghuan Shi, Yang Gao, Zhonghai Lu, Qinghong Shen, Li Li, Hongbing Pan
Format: Article
Language:English
Published: MDPI AG 2019-01-01
Series:Electronics
Subjects:
hardware acceleration
deep neural networks (DNNs)
fully-connected layers
network compression
VLSI
Online Access:http://www.mdpi.com/2079-9292/8/1/78

Internet

http://www.mdpi.com/2079-9292/8/1/78

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