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cs.AR2020★ 8 cited
Understanding Training Efficiency of Deep Learning Recommendation Models at Scale
Bilge Acun, Matthew Murphy, Xiaodong Wang +3
The use of GPUs has proliferated for machine learning workflows and is now considered mainstream for many deep learning models. Meanwhile, when training state-of-the-art personal r…
cs.AR2020
Enabling Compute-Communication Overlap in Distributed Deep Learning Training Platforms
Saeed Rashidi, Matthew Denton, Srinivas Sridharan +4
Deep Learning (DL) training platforms are built by interconnecting multiple DL accelerators (e.g., GPU/TPU) via fast, customized interconnects with 100s of gigabytes (GBs) of bandw…