Accelerating Distributed Learning in Non-Dedicated Environments
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Cloud Computing"
DOI: 10.1109/tcc.2021.3102593
Abstract: Machine learning (ML) models are increasingly trained with distributed workers possessing heterogeneous resources. In such scenarios, model training efficiency may be negatively affected by stragglers—workers that run much slower than others. Efficient model training requires… read more here.
Keywords: accelerating distributed; learning non; load; dedicated environments ... See more keywords
DIESEL+: Accelerating Distributed Deep Learning Tasks on Image Datasets
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Parallel and Distributed Systems"
DOI: 10.1109/tpds.2021.3104252
Abstract: We observe that data access and processing takes a significant amount of time in large-scale deep learning training tasks (DLTs) on image datasets. Three factors contribute to this problem: (1) the massive and recurrent accesses… read more here.
Keywords: accelerating distributed; deep learning; image datasets; diesel accelerating ... See more keywords