FSP: Towards Flexible Synchronous Parallel Frameworks for Distributed Machine Learning-Reference-Cited by-同舟云学术

FSP: Towards Flexible Synchronous Parallel Frameworks for Distributed Machine Learning

Author:

Wang Zhigang¹^ORCID,Tu Yilei¹,Wang Ning¹^ORCID,Gao Lixin²^ORCID,Nie Jie¹^ORCID,Wei Zhiqiang¹,Gu Yu³^ORCID,Yu Ge³^ORCID

Affiliation:

1. Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China

2. Department of Electrical and Computer Engineering, University of Massachusetts Amherst, Amherst, MA, USA

3. School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

National Key Research and Development Program of China

National Science Foundation

Computer Department of Ocean University of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Signal Processing

Link

Reference57 articles.

5. Revisiting distributed synchronous SGD;pan,2017

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4. A Synchronous Parallel Method with Parameters Communication Prediction for Distributed Machine Learning;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2024