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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
6731
Venue
SIGMOD
Year
2023
Pagerank
8.2750247e-05
Overall Rank
2,668 | 81.70%
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 17 of 17 citing papers.

Rank Citing Paper Year Venue Pagerank
4,878 NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams 2024 VLDB 6.4684388e-05
5,079 NeutronOrch: Rethinking Sample-based GNN Training under CPU-GPU Heterogeneous Environments 2024 VLDB 6.3717342e-05
5,205 ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs 2024 VLDB 6.318626e-05
5,316 Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective 2024 VLDB 6.2687017e-05
6,630 Efficient Training of Graph Neural Networks on Large Graphs 2024 VLDB 5.8192133e-05
6,652 Eliminating Data Processing Bottlenecks in GNN Training over Large Graphs via Two-level Feature Compression 2024 VLDB 5.8139657e-05
6,730 SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement 2024 SIGMOD 5.7895038e-05
6,900 Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving 2025 SIGMOD 5.7430032e-05
7,087 DAHA: Accelerating GNN Training with Data and Hardware Aware Execution Planning 2024 VLDB 5.7069166e-05
7,374 ADGNN: Towards Scalable GNN Training with Aggregation-Difference Aware Sampling 2023 SIGMOD 5.6306367e-05
9,881 The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format 2024 SIGMOD 5.2040783e-05
10,323 NeutronHeter: Optimizing Distributed Graph Neural Network Training for Heterogeneous Clusters 2026 SIGMOD 5.093636e-05
10,373 Gem: Scalable Monotonic Graph Processing Beyond Billion-Scale on a Single Machine 2026 SIGMOD 5.093636e-05
10,521 Efficient GNN Training on Giant Graphs with Collective Batching and Scheduling 2026 VLDB 5.093636e-05
10,811 Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch 2025 VLDB 5.093636e-05
10,835 NeutronTask: Scalable and Efficient Multi-GPU GNN Training with Task Parallelism 2025 VLDB 5.093636e-05
10,975 Faster Convergence in Mini-batch Graph Neural Networks Training with Pseudo Full Neighborhood Compensation 2025 VLDB 5.093636e-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
389 One Trillion Edges: Graph Processing at Facebook-Scale 2015 VLDB 0.00019386526
1,132 SANCUS: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks 2022 VLDB 0.00012041292
1,234 Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture 2021 VLDB 0.00011549432
Previous Page 1 / 1 Next

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