Improving Scalability of Parallel CNN Training by Adaptively Adjusting Parameter Update Frequency
Journal of Parallel and Distributed Computing (JPDC), 2022
This study proposes a partial-model update frequency adjustment method which is designed to reduce the communication cost in centralized parallel training.
BibTeX
@article{lee2022improving,
title={Improving scalability of parallel CNN training by adaptively adjusting parameter update frequency},
author={Lee, Sunwoo and Kang, Qiao and Al-Bahrani, Reda and Agrawal, Ankit and Choudhary, Alok and Liao, Wei-Keng},
journal={Journal of Parallel and Distributed Computing},
volume={159},
pages={10--23},
year={2022},
publisher={Elsevier}
}