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Approximate Gradient Synchronization with AQGB

Published:07 November 2023Publication History

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References

  1. Yanghua Peng, Yibo Zhu, Yangrui Chen, Yixin Bao, Bairen Yi, Chang Lan, Chuan Wu, and Chuanxiong Guo. 2019. A Generic Communication Scheduler for Distributed DNN Training Acceleration. In 27th SOSP(Huntsville, Ontario, Canada). ACM, New York, NY, USA, 16–29.Google ScholarGoogle Scholar
  2. Jiaxiang Wu, Weidong Huang, Junzhou Huang, and Tong Zhang. 2018. Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization. In 35th ICML, Vol. 80. PMLR, 5325–5333.Google ScholarGoogle Scholar
  3. Hang Xu, Chen-Yu Ho, Ahmed M. Abdelmoniem, Aritra Dutta, El Houcine Bergou, Konstantinos Karatsenidis, Marco Canini, and Panos Kalnis. 2021. GRACE: A Compressed Communication Framework for Distributed Machine Learning. In 41st ICDCS. 561–572.Google ScholarGoogle Scholar

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  1. Approximate Gradient Synchronization with AQGB

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      cover image ACM Other conferences
      APNet '22: Proceedings of the 6th Asia-Pacific Workshop on Networking
      July 2022
      110 pages
      ISBN:9781450397483
      DOI:10.1145/3542637

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      Publication History

      • Published: 7 November 2023

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