2 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.NI2023★ 2 cited
Rethinking Machine Learning Collective Communication as a Multi-Commodity Flow Problem
Behnaz Arzani, Siva Kesava Reddy Kakarla, Miguel Castro +3
We show communication schedulers' recent work proposed for ML collectives does not scale to the increasing problem sizes that arise from training larger models. These works also of…
cs.DC2023★ 2 cited
SuperScaler: Supporting Flexible DNN Parallelization via a Unified Abstraction
Zhiqi Lin, Youshan Miao, Guodong Liu +10
With the growing model size, deep neural networks (DNN) are increasingly trained over massive GPU accelerators, which demands a proper parallelization plan that transforms a DNN mo…