G3: When Graph Neural Networks Meet Parallel Graph Processing Systems on GPUs
Summary: G3 recasts GNN training as GPU parallel graph processing, exposing flexible C/C++ APIs and reusable GNN primitives. Its runtime automatically applies graph-centric optimizations, achieving higher performance than PyTorch and TensorFlow. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Husong Liu (National University of Singapore)
- 2. Shengliang Lu (National University of Singapore)
- 3. Xinyu Chen (National University of Singapore)
- 4. Bingsheng He (National University of Singapore)
BibTeX Citation
@article{liu_vldb20,
title = {{G3: When Graph Neural Networks Meet Parallel Graph Processing Systems on GPUs}},
author = {Liu, Husong and Lu, Shengliang and Chen, Xinyu and He, Bingsheng},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {12},
pages = {2813--2816},
doi = {10.14778/3415478.3415482},
url = {https://doi.org/10.14778/3415478.3415482},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,134 | SANCUS: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks | 2022 | VLDB | 0.00011893521 |
| 2,279 | NeutronStar: Distributed GNN Training with Hybrid Dependency Management | 2022 | SIGMOD | 8.7062637e-05 |
| 4,622 | Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning | 2022 | VLDB | 6.4982876e-05 |
| 5,899 | Lotan: Bridging the Gap between GNNs and Scalable Graph Analytics Engines | 2023 | VLDB | 5.9545431e-05 |
| 8,670 | Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense | 2024 | VLDB | 5.2917782e-05 |
| 9,233 | Can Graph Reordering Speed Up Graph Neural Network Training? An Experimental Study | 2025 | VLDB | 5.2056825e-05 |
| 9,900 | Scalable Graph Convolutional Network Training on Distributed-Memory Systems | 2023 | VLDB | 5.1116429e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3 | Pregel: A System for Large-Scale Graph Processing | 2010 | SIGMOD | 0.0012092602 |
| 4,237 | Accelerating Dynamic Graph Analytics on GPUs | 2018 | VLDB | 6.7107028e-05 |
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| 9 | 6,669 | Efficient Training of Graph Neural Networks on Large Graphs | 2024 | VLDB |
| 10 | 2,596 | Scalable and Efficient Full-Graph GNN Training for Large Graphs | 2023 | SIGMOD |