2 citations · 7 across the 5 of their papers we have counts for
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cs.DC2024
CDFGNN: a Systematic Design of Cache-based Distributed Full-Batch Graph Neural Network Training with Communication Reduction
Shuai Zhang, Zite Jiang, Haihang You
Graph neural network training is mainly categorized into mini-batch and full-batch training methods. The mini-batch training method samples subgraphs from the original graph in eac…
cs.DC2020★ 1 cited
An Efficient and Balanced Graph Partition Algorithm for the Subgraph-Centric Programming Model on Large-scale Power-law Graphs
Shuai Zhang, Zite Jiang, Xingzhong Hou +3
The subgraph-centric programming model is a promising approach and has been applied in many state-of-the-art distributed graph computing frameworks. However, traditional graph part…
cs.DC2019★ 2 cited
DRONE: a Distributed Subgraph-Centric Framework for Processing Large Scale Power-law Graphs
Xiaole Wen, Shuai Zhang, Haihang You
Nowadays, in the big data era, social networks, graph databases, knowledge graphs, electronic commerce etc. demand efficient and scalable capability to process an ever increasing v…