Efficient All-Reduce for Distributed DNN Training in Optical Interconnect Systems-Reference-Cited by-同舟云学术

Efficient All-Reduce for Distributed DNN Training in Optical Interconnect Systems

Published:2023-02-21 Issue: Volume: Page:
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Container-title:Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming
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Author:

Dai Fei¹,Chen Yawen¹,Huang Zhiyi¹,Zhang Haibo¹,Zhang Fangfang²

Affiliation:

1. University of Otago, Dunedin, New Zealand

2. Qilu University of Technology, Jinan, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3572848.3577391

Reference15 articles.

1. Near-Optimal Topology-adaptive Parameter Synchronization in Distributed DNN Training

2. Communication Algorithm-Architecture Co-Design for Distributed Deep Learning

3. Guanhua Wang , Shivaram Venkataraman , Amar Phanishayee , Jorgen Thelin , Nikhil Devanur , and Ion Stoica . Blink: Fast and generic collectives for distributed ml. arXiv preprint arXiv:1910.04940 , 2019 . Guanhua Wang, Shivaram Venkataraman, Amar Phanishayee, Jorgen Thelin, Nikhil Devanur, and Ion Stoica. Blink: Fast and generic collectives for distributed ml. arXiv preprint arXiv:1910.04940, 2019.

4. Multidomain Inter/Intrachip Silicon Photonic Networks for Energy-Efficient Rack-Scale Computing Systems

5. Bandwidth optimal all-reduce algorithms for clusters of workstations

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1. Communication-efficient ADMM-based distributed algorithms for sparse training;Neurocomputing;2023-09

2. Wrht: Efficient All-reduce for Distributed DNN Training in Optical Interconnect Systems;Proceedings of the 52nd International Conference on Parallel Processing;2023-08-07