45 citations · 135 across the 13 of their papers we have counts for
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cs.DC2025
MegaScale-Data: Scaling Dataloader for Multisource Large Foundation Model Training
Juntao Zhao, Qi Lu, Wei Jia +13
Modern frameworks for training large foundation models (LFMs) employ dataloaders in a data-parallel manner, with each loader processing a disjoint subset of training data. When pre…
cs.DC2022
dPRO: A Generic Profiling and Optimization System for Expediting Distributed DNN Training
Hanpeng Hu, Chenyu Jiang, Yuchen Zhong +5
Distributed training using multiple devices (e.g., GPUs) has been widely adopted for learning DNN models over large datasets. However, the performance of large-scale distributed tr…
cs.DC2018★ 13 cited
Online Job Scheduling in Distributed Machine Learning Clusters
Yixin Bao, Yanghua Peng, Chuan Wu +1
Nowadays large-scale distributed machine learning systems have been deployed to support various analytics and intelligence services in IT firms. To train a large dataset and derive…