Expediting Distributed DNN Training With Device Topology-Aware Graph Deployment

Author:

Zhang Shiwei1ORCID,Yi Xiaodong1ORCID,Diao Lansong2,Wu Chuan1ORCID,Wang Siyu2,Lin Wei2

Affiliation:

1. Department of Computer Science, University of Hong Kong, Pokfulam, Hong Kong

2. Alibaba Group, Hangzhou, Zhejiang, China

Funder

Alibaba Group

Hong Kong RGC

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Signal Processing

Reference55 articles.

1. Nccl 2.0;jeaugey;Proc GPU Technol Conf,2017

2. Horovod: Fast and easy distributed deep learning in tensorflow;sergeev,2018

3. A unified architecture for accelerating distributed {DNN} training in heterogeneous GPU/CPU clusters;jiang;Proc 14th USENIX Symp Operating Syst Des Implementation,2020

4. Scaling Distributed Machine Learning with the Parameter Server

5. Post: Device placement with cross-entropy minimization and proximal policy optimization;gao;Proc Adv Neural Inf Process Syst,2018

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