BPB-GNN: Resource-Efficient Distributed GNN Training via Boundary-Aware Prefetching and Cost-Balanced Batch Construction
Distributed graph neural network (GNN) training is essential for large-scale graph learning, but existing mini-batch frameworks still suffer from substantial inter-partition communication overhead and indirect, coarse-grained GPU memory control. In distributed mini-batch training, remote sampled neighbors cause frequen...