KubFBS: A fine‐grained and balance‐aware scheduling system for deep learning tasks based on kubernetes-Reference-Cited by-同舟云学术

KubFBS: A fine‐grained and balance‐aware scheduling system for deep learning tasks based on kubernetes

Published:2022-01-24 Issue:11 Volume:34 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency and Computation

Author:

Liu Zijie¹²^ORCID,Chen Can¹²,Li Junjiang¹²,Cheng Yi¹²,Kou Yingjie²³,Zhang Dengyin¹²

Affiliation:

1. School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing People's Republic of China

2. Jiangsu Key Laboratory of Broadband Wireless Communication and Internet of Things Nanjing University of Posts and Telecommunications Nanjing People's Republic of China

3. College of Telecommunications & Information Engineering Nanjing University of Posts and Telecommunications Nanjing People's Republic of China

Funder

Nanjing University of Posts and Telecommunications

Government of Jiangsu Province

ASCRS Research Foundation

National Natural Science Foundation of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6836

Reference33 articles.

1. DehazeNet: An End-to-End System for Single Image Haze Removal

2. s-LWSR: Super Lightweight Super-Resolution Network

3. JsrNet: A Joint Sampling–Reconstruction Framework for Distributed Compressive Video Sensing

4. A Survey of the Usages of Deep Learning for Natural Language Processing

5. SecureNLP: A System for Multi-Party Privacy-Preserving Natural Language Processing

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