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}
}