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: h88e6eb5e29240e2e
Venue: SIGMOD
Year: 2023
Pagerank: 6.32357e-05
Overall Rank: 4,993 | 66.44%
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
5,310	DynaHB: A Communication-Avoiding Asynchronous Distributed Framework with Hybrid Batches for Dynamic GNN Training	2024	VLDB	6.1857447e-05
10,535	SWIFT: Enabling Large-Scale Temporal Graph Learning on a Single Machine	2026	SIGMOD	4.9793485e-05
10,737	FlareDTDG: Harnessing Temporal Recency for Scalable Discrete-Time Dynamic Graph Training	2026	VLDB	4.9793485e-05
11,198	SWASH: A Flexible Communication Framework with Sliding Window-Based Cache Sharing for Scalable DGNN Training	2025	SIGMOD	4.9793485e-05
11,361	Faster Convergence in Mini-batch Graph Neural Networks Training with Pseudo Full Neighborhood Compensation	2025	VLDB	4.9793485e-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
211	AliGraph: A Comprehensive Graph Neural Network Platform	2019	VLDB	0.00024816965
1,033	AGL: A Scalable System for Industrial-purpose Graph Machine Learning	2020	VLDB	0.00012397734
1,134	SANCUS: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks	2022	VLDB	0.00011893521
1,364	TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs	2022	VLDB	0.00010914152
2,279	NeutronStar: Distributed GNN Training with Hybrid Dependency Management	2022	SIGMOD	8.7062637e-05
2,519	HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework	2022	VLDB	8.3521095e-05
6,674	Reliable Data Distillation on Graph Convolutional Network	2020	SIGMOD	5.7125691e-05

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