102 citations · 340 across the 23 of their papers we have counts for
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cs.DC2022★ 7 cited
MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platforms
Yuke Wang, Boyuan Feng, Zheng Wang +4
The increasing size of input graphs for graph neural networks (GNNs) highlights the demand for using multi-GPU platforms. However, existing multi-GPU GNN systems optimize the compu…
cs.DC2022★ 43 cited
Dynamic GPU Energy Optimization for Machine Learning Training Workloads
Farui Wang, Weizhe Zhang, Shichao Lai +2
GPUs are widely used to accelerate the training of machine learning workloads. As modern machine learning models become increasingly larger, they require a longer time to train, le…