DGC: Training Dynamic Graphs with Spatio-Temporal Non-Uniformity using Graph Partitioning by Chunks

Summary: Chunk-based partitioning of dynamic graphs with graph coarsening to balance DGNN workloads under non-uniform spatio-temporal sparsity. Chunk fusion and adaptive stale aggregation yield 1.25x–7.52x speedups over state-of-the-art DGNN training on 3 models and 4 datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6801
Venue: SIGMOD
Year: 2023
Pagerank: 6.4581865e-05
Overall Rank: 4,891 | 66.45%
DOI: 10.1145/3626724

Incoming Non-self Citations Over Time

Authors

1. Fahao Chen (University of Aizu)
2. Peng Li (University of Aizu)
3. Celimuge Wu (University of Electro-Communications)

BibTeX Citation

@inproceedings{chen_sigmod23,
        title = {{DGC: Training Dynamic Graphs with Spatio-Temporal Non-Uniformity using Graph Partitioning by Chunks}},
        author = {Chen, Fahao and Li, Peng and Wu, Celimuge},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3626724},
        url = {https://dl.acm.org/doi/10.1145/3626724},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 5 of 5 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
5,760	DynaHB: A Communication-Avoiding Asynchronous Distributed Framework with Hybrid Batches for Dynamic GNN Training	2024	VLDB	6.0961929e-05
10,330	SWIFT: Enabling Large-Scale Temporal Graph Learning on a Single Machine	2026	SIGMOD	5.093636e-05
10,555	FlareDTDG: Harnessing Temporal Recency for Scalable Discrete-Time Dynamic Graph Training	2026	VLDB	5.093636e-05
10,780	SWASH: A Flexible Communication Framework with Sliding Window-Based Cache Sharing for Scalable DGNN Training	2025	SIGMOD	5.093636e-05
10,975	Faster Convergence in Mini-batch Graph Neural Networks Training with Pseudo Full Neighborhood Compensation	2025	VLDB	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
223	AliGraph: A Comprehensive Graph Neural Network Platform	2019	VLDB	0.00024182473
1,048	AGL: A Scalable System for Industrial-purpose Graph Machine Learning	2020	VLDB	0.00012433693
1,132	SANCUS: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks	2022	VLDB	0.00012041292
1,409	TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs	2022	VLDB	0.00010854808
2,485	HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework	2022	VLDB	8.5145736e-05
2,695	NeutronStar: Distributed GNN Training with Hybrid Dependency Management	2022	SIGMOD	8.2468134e-05
6,550	Reliable Data Distillation on Graph Convolutional Network	2020	SIGMOD	5.8430465e-05

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