Modeling and Optimizing the Scaling Performance in Distributed Deep Learning Training.

Ting Liu|Tianhao Miao|Qinghua Wu|Zhenyu Li|Guangxin He|Jiaoren Wu|Shengzhuo Zhang|Xingwu Yang|Gareth Tyson|Gaogang Xie


Anthology ID:DBLP:conf/www/LiuMW0HWZYTX22
Volume:WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25 - 29, 2022
Year:2022
Venue:The Web Conference (WWW)
Publisher:ACM
Pages:1764-1773
URL:https://doi.org/10.1145/3485447.3511981
DOI:https://doi.org/10.1145/3485447.3511981
DBLP:conf/www/LiuMW0HWZYTX22
BibTeX:
@inproceedings{liu-2022-modeling, author = {Ting Liu and Tianhao Miao and Qinghua Wu and Zhenyu Li and Guangxin He and Jiaoren Wu and Shengzhuo Zhang and Xingwu Yang and Gareth Tyson and Gaogang Xie}, editor = {Fr\'{e}d\'{e}rique Laforest and Rapha\"{e}l Troncy and Elena Simperl and Deepak Agarwal and Aristides Gionis and Ivan Herman and Lionel M\'{e}dini}, title = {{Modeling and Optimizing the Scaling Performance in Distributed Deep Learning Training}}, booktitle = {{WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25 - 29, 2022}}, pages = {1764--1773}, publisher = {ACM}, year = {2022}, url = {https://doi.org/10.1145/3485447.3511981}, doi = {https://doi.org/10.1145/3485447.3511981} }