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DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with the GPU

Summary: DUCATI introduces a Dual-Cache system for GNNs on giant graphs, adding an Adj-Cache to exploit adjacency locality and accelerate mini-batch generation on GPUs. A workload-aware allocator tunes cache allocation; on 4B graphs, yields up to 3.3x speedups over DGL, with time–accuracy trade-offs analyzed. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hdc343db641070cf0
Venue
SIGMOD
Year
2023
Pagerank
8.3735089e-05
Overall Rank
2,506 | 83.16%
DOI
10.1145/3589311

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zhang_sigmod23,
        title = {{DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with the GPU}},
        author = {Zhang, Xin and Shen, Yanyan and Shao, Yingxia and Chen, Lei},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3589311},
        url = {https://dl.acm.org/doi/10.1145/3589311},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 18 of 18 citing papers.

Rank Citing Paper Year Venue Pagerank
4,504 NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams 2024 VLDB 6.5709602e-05
4,767 ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs 2024 VLDB 6.4245781e-05
4,827 DAHA: Accelerating GNN Training with Data and Hardware Aware Execution Planning 2024 VLDB 6.3893293e-05
4,855 NeutronOrch: Rethinking Sample-based GNN Training under CPU-GPU Heterogeneous Environments 2024 VLDB 6.377545e-05
4,899 Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective 2024 VLDB 6.3628105e-05
6,168 Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving 2025 SIGMOD 5.8603375e-05
6,673 Efficient Training of Graph Neural Networks on Large Graphs 2024 VLDB 5.7120259e-05
6,785 Eliminating Data Processing Bottlenecks in GNN Training over Large Graphs via Two-level Feature Compression 2024 VLDB 5.6811551e-05
6,831 SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement 2024 SIGMOD 5.6673474e-05
7,511 ADGNN: Towards Scalable GNN Training with Aggregation-Difference Aware Sampling 2023 SIGMOD 5.5044293e-05
7,527 NeutronTask: Scalable and Efficient Multi-GPU GNN Training with Task Parallelism 2025 VLDB 5.499936e-05
9,802 NeutronHeter: Optimizing Distributed Graph Neural Network Training for Heterogeneous Clusters 2026 SIGMOD 5.1233734e-05
10,048 The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format 2024 SIGMOD 5.0896901e-05
10,263 Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch 2025 VLDB 5.0480912e-05
10,582 Gem: Scalable Monotonic Graph Processing Beyond Billion-Scale on a Single Machine 2026 SIGMOD 4.9769913e-05
10,716 Efficient GNN Training on Giant Graphs with Collective Batching and Scheduling 2026 VLDB 4.9769913e-05
10,828 ThunderGNN: Unlocking Tensor Cores for Graph Neural Networks 2026 VLDB 4.9769913e-05
11,368 Faster Convergence in Mini-batch Graph Neural Networks Training with Pseudo Full Neighborhood Compensation 2025 VLDB 4.9769913e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank Cited Paper Year Venue Pagerank
394 One Trillion Edges: Graph Processing at Facebook-Scale 2015 VLDB 0.00019182322
1,134 SANCUS: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks 2022 VLDB 0.0001188789
1,227 Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture 2021 VLDB 0.0001144428
Previous Page 1 / 1 Next

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