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)
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 |
|---|---|---|---|---|
| 5,332 | DynaHB: A Communication-Avoiding Asynchronous Distributed Framework with Hybrid Batches for Dynamic GNN Training | 2024 | VLDB | 6.1623722e-05 |
| 10,611 | SWIFT: Enabling Large-Scale Temporal Graph Learning on a Single Machine | 2026 | SIGMOD | 4.9605343e-05 |
| 10,808 | FlareDTDG: Harnessing Temporal Recency for Scalable Discrete-Time Dynamic Graph Training | 2026 | VLDB | 4.9605343e-05 |
| 11,266 | SWASH: A Flexible Communication Framework with Sliding Window-Based Cache Sharing for Scalable DGNN Training | 2025 | SIGMOD | 4.9605343e-05 |
| 11,421 | Faster Convergence in Mini-batch Graph Neural Networks Training with Pseudo Full Neighborhood Compensation | 2025 | VLDB | 4.9605343e-05 |
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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 |
|---|---|---|---|---|
| 203 | AliGraph: A Comprehensive Graph Neural Network Platform | 2019 | VLDB | 0.00025234479 |
| 1,021 | AGL: A Scalable System for Industrial-purpose Graph Machine Learning | 2020 | VLDB | 0.00012408574 |
| 1,047 | SANCUS: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks | 2022 | VLDB | 0.00012313386 |
| 1,372 | TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs | 2022 | VLDB | 0.00010873001 |
| 2,273 | NeutronStar: Distributed GNN Training with Hybrid Dependency Management | 2022 | SIGMOD | 8.7079974e-05 |
| 2,525 | HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework | 2022 | VLDB | 8.3302991e-05 |
| 6,693 | Reliable Data Distillation on Graph Convolutional Network | 2020 | SIGMOD | 5.6909845e-05 |
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