Interference-aware opportunistic job placement for shared distributed deep learning clusters-Reference-Cited by-同舟云学术

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Interference-aware opportunistic job placement for shared distributed deep learning clusters

Published:2024-01 Issue: Volume:183 Page:104776
ISSN:0743-7315
Container-title:Journal of Parallel and Distributed Computing
language:en
Short-container-title:Journal of Parallel and Distributed Computing

Author:

Li Hongliang^ORCID,Zhao Hairui,Sun Ting,Li Xiang^ORCID,Xu Haixiao,Li Keqin

Funder

National Key Research and Development Program of China

Natural Science Foundation of Jilin Province

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture,Theoretical Computer Science,Software

Reference51 articles.

1. TensorFlow: large-scale machine learning on heterogeneous distributed systems;Abadi,2016

2. Deep learning-based job placement in distributed machine learning clusters;Bao,2019

3. Balancing stragglers against staleness in distributed deep learning;Basu,2018

4. Borg, Omega, and Kubernetes;Burns;Commun. ACM,2016

5. Semi-dynamic load balancing: efficient distributed learning in non-dedicated environments;Chen,2020

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