HiTDL: High-Throughput Deep Learning Inference at the Hybrid Mobile Edge-Reference-Cited by-同舟云学术

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HiTDL: High-Throughput Deep Learning Inference at the Hybrid Mobile Edge

Published:2022-12-01 Issue:12 Volume:33 Page:4499-4514
ISSN:1045-9219
Container-title:IEEE Transactions on Parallel and Distributed Systems
language:
Short-container-title:IEEE Trans. Parallel Distrib. Syst.

Author:

Wu Jing¹^ORCID,Wang Lin²^ORCID,Pei Qiangyu¹^ORCID,Cui Xingqi¹,Liu Fangming¹^ORCID,Yang Tingting³

Affiliation:

1. National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China

2. VU Amsterdam, Amsterdam, The Netherlands

3. Peng Cheng Laboratory, Shenzhen, China

Funder

National Natural Science Foundation of China

National Key Research & Development (R&D) Plan

DFG

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/71/9790018/09847073.pdf?arnumber=9847073

Reference65 articles.

1. Edge Assisted Real-time Object Detection for Mobile Augmented Reality

3. λDNN: Achieving Predictable Distributed DNN Training With Serverless Architectures

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