NeutronStar: Distributed GNN Training with Hybrid Dependency Management
Summary: Hybrid dependency management for distributed GNN training; adaptively blends cached and communicated dependencies at runtime. NeutronStar automates GNN training with CPU-GPU optimizations, delivering 1.81×–14.25× speedup vs DistDGL/ROC on 16-node Aliyun. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Qiange Wang (Northeastern University)
- 2. Yanfeng Zhang (Northeastern University)
- 3. Hao Wang (International Digital Economy Academy)
- 4. Chaoyi Chen (Northeastern University)
- 5. Xiaodong Zhang (Ohio State University)
- 6. Ge Yu (Northeastern University)
BibTeX Citation
@inproceedings{wang_sigmod22,
title = {{NeutronStar: Distributed GNN Training with Hybrid Dependency Management}},
author = {Wang, Qiange and Zhang, Yanfeng and Wang, Hao and Chen, Chaoyi and Zhang, Xiaodong and Yu, Ge},
series = {{SIGMOD} '22},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3514221.3526134},
url = {https://dl.acm.org/doi/10.1145/3514221.3526134},
year = {2022}
}Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 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 |
| 526 | PyTorch Distributed: Experiences on Accelerating Data Parallel Training | 2020 | VLDB | 0.00016866695 |
| 902 | Parallelizing Sequential Graph Computations | 2017 | SIGMOD | 0.00013142001 |
| 1,021 | AGL: A Scalable System for Industrial-purpose Graph Machine Learning | 2020 | VLDB | 0.00012408574 |
| 1,223 | Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture | 2021 | VLDB | 0.00011439503 |
| 3,316 | A Distributed Multi-GPU System for Fast Graph Processing | 2018 | VLDB | 7.415249e-05 |
| 3,321 | Accelerating Triangle Counting on GPU | 2021 | SIGMOD | 7.4117038e-05 |
| 3,706 | G3: When Graph Neural Networks Meet Parallel Graph Processing Systems on GPUs | 2020 | VLDB | 7.0605656e-05 |
| 6,325 | Automating Incremental and Asynchronous Evaluation for Recursive Aggregate Data Processing | 2020 | SIGMOD | 5.7957351e-05 |
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