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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
8.3774747e-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
4,502 NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams 2024 VLDB 6.5740722e-05
4,764 ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs 2024 VLDB 6.4276208e-05
4,825 DAHA: Accelerating GNN Training with Data and Hardware Aware Execution Planning 2024 VLDB 6.3923554e-05
4,853 NeutronOrch: Rethinking Sample-based GNN Training under CPU-GPU Heterogeneous Environments 2024 VLDB 6.3805655e-05
4,898 Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective 2024 VLDB 6.365824e-05
6,166 Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving 2025 SIGMOD 5.8631131e-05
6,669 Efficient Training of Graph Neural Networks on Large Graphs 2024 VLDB 5.7147311e-05
6,780 Eliminating Data Processing Bottlenecks in GNN Training over Large Graphs via Two-level Feature Compression 2024 VLDB 5.6838458e-05
6,826 SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement 2024 SIGMOD 5.6700316e-05
7,506 ADGNN: Towards Scalable GNN Training with Aggregation-Difference Aware Sampling 2023 SIGMOD 5.5070363e-05
7,522 NeutronTask: Scalable and Efficient Multi-GPU GNN Training with Task Parallelism 2025 VLDB 5.5025409e-05
9,795 NeutronHeter: Optimizing Distributed Graph Neural Network Training for Heterogeneous Clusters 2026 SIGMOD 5.1257999e-05
10,043 The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format 2024 SIGMOD 5.0921006e-05
10,257 Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch 2025 VLDB 5.050482e-05
10,571 Gem: Scalable Monotonic Graph Processing Beyond Billion-Scale on a Single Machine 2026 SIGMOD 4.9793485e-05
10,706 Efficient GNN Training on Giant Graphs with Collective Batching and Scheduling 2026 VLDB 4.9793485e-05
10,818 ThunderGNN: Unlocking Tensor Cores for Graph Neural Networks 2026 VLDB 4.9793485e-05
11,361 Faster Convergence in Mini-batch Graph Neural Networks Training with Pseudo Full Neighborhood Compensation 2025 VLDB 4.9793485e-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 0.00019191286
1,134 SANCUS: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks 2022 VLDB 0.00011893521
1,224 Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture 2021 VLDB 0.000114497
Previous Page 1 / 1 Next

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