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cs.DC2024
HopGNN: Boosting Distributed GNN Training Efficiency via Feature-Centric Model Migration
Weijian Chen, Shuibing He, Haoyang Qu +1
Distributed training of graph neural networks (GNNs) has become a crucial technique for processing large graphs. Prevalent GNN frameworks are model-centric, necessitating the trans…
cs.DC2024
Optimizing Large Model Training through Overlapped Activation Recomputation
Ping Chen, Wenjie Zhang, Shuibing He +10
Large model training often uses recomputation to alleviate memory pressure and pipelines to exploit the parallelism of data, tensors, and devices. However, existing recomputation a…