DistrEdge: Speeding up Convolutional Neural Network Inference on Distributed Edge Devices

As the number of edge devices with computing resources (e.g., embedded GPUs, mobile phones, and laptops) in-creases, recent studies demonstrate that it can be beneficial to col-laboratively run convolutional neural network (CNN) inference on more than one edge device. However, these studies make str...

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Bibliographic Details

Published in:	Proceedings - IEEE International Parallel and Distributed Processing Symposium pp. 1097 - 1107
Main Authors:	Hou, Xueyu, Guan, Yongjie, Han, Tao, Zhang, Ning
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.05.2022
Subjects:	Adaptive systems Computational modeling convolutional neural net-work deep reinforcement learning distributed computing Distributed processing Distribution strategy edge computing Laboratories Portable computers Reinforcement learning
ISSN:	1530-2075
Online Access:	Get full text
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