Sparse convolutional neural network acceleration with lossless input feature map compression for resource‐constrained systems

Sparse convolutional neural network acceleration with lossless input feature map compression for resource‐constrained systems

Abstract Many recent research efforts have exploited data sparsity for the acceleration of convolutional neural network (CNN) inferences. However, the effects of data transfer between main memory and the CNN accelerator have been largely overlooked. In this work, the authors propose a CNN accelerati...

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Bibliographic Details
Main Authors: Jisu Kwon, Joonho Kong, Arslan Munir
Format: Article
Language:English
Published: Hindawi-IET 2022-01-01
Series:IET Computers & Digital Techniques
Subjects:
accelerator
compression
convolutional neural networks
field programmable gate array
input sparsity
Online Access:https://doi.org/10.1049/cdt2.12038

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