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cs.DC2026
GreenGNN: Energy-Aware Windowed Communication Optimization for Distributed GNN Training
Arefin Niam, Tevfik Kosar, M. S. Q. Zulkar Nine
Large-scale graph neural network (GNN) training often requires distributed clusters because graph structure and feature tensors no longer fit in a single node's memory. In sampling…
cs.DC2026
GreenDyGNN: Runtime-Adaptive Energy-Efficient Communication for Distributed GNN Training
Arefin Niam, Tevfik Kosar, M. S. Q. Zulkar Nine
Distributed GNN training is dominated by remote feature fetching, which can be very costly. Multi-hop neighborhood sampling crosses partition boundaries and triggers fine-grained R…
cs.DC2026
A Periodic Space of Distributed Computing: Vision & Framework
Mohsen Amini Salehi, Adel N. Tousi, Hai Duc Nguyen +5
Advances in networking and computing technologies throughout the early decades of the 21st century have transformed long-standing dreams of pervasive communication and computation…