SIGMA is a unified streaming graph partitioner supporting configurable vertex- and edge-balanced partitioning for distributed GNN training across different system architectures.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.DC 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
FeLoG achieves 27.9x average speedup and over 53% communication reduction in distributed graph embedding by using feedback-coupled sampling, activity-aware communication, and round-interleaved pipelining.
citing papers explorer
-
SIGMA: A Versatile Streaming Graph Partitioner for Vertex- and Edge-Balanced Distributed GNN Training
SIGMA is a unified streaming graph partitioner supporting configurable vertex- and edge-balanced partitioning for distributed GNN training across different system architectures.
-
FeLoG: Scalable and Efficient Distributed Graph Embedding with Feedback Loop Mechanism
FeLoG achieves 27.9x average speedup and over 53% communication reduction in distributed graph embedding by using feedback-coupled sampling, activity-aware communication, and round-interleaved pipelining.