2 citations · 3 across the 5 of their papers we have counts for
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cs.DC2023★ 2 cited
NeutronOrch: Rethinking Sample-based GNN Training under CPU-GPU Heterogeneous Environments
Xin Ai, Qiange Wang, Chunyu Cao +5
Graph Neural Networks (GNNs) have demonstrated outstanding performance in various applications. Existing frameworks utilize CPU-GPU heterogeneous environments to train GNN models a…
cs.LG2023
NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams
Chaoyi Chen, Dechao Gao, Yanfeng Zhang +6
Existing Graph Neural Network (GNN) training frameworks have been designed to help developers easily create performant GNN implementations. However, most existing GNN frameworks as…
cs.LG2023★ 1 cited
Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective
Hao Yuan, Yajiong Liu, Yanfeng Zhang +5
Many Graph Neural Network (GNN) training systems have emerged recently to support efficient GNN training. Since GNNs embody complex data dependencies between training samples, the…