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TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs

Summary: TGL unifies configurable temporal GNN training with scalable sampling, memory, and message-passing components. Temporal-CSR, parallel sampling, and random-chunk scheduling enable billion-edge, multi-GPU training—up to 13× faster than prior implementations. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
h4e32c3795ee4090e
Venue
VLDB
Year
2022
Pagerank
0.00010914152
Overall Rank
1,364 | 90.84%
DOI
10.14778/3529337.3529342

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{zhou_vldb22,
        title = {{TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs}},
        author = {Zhou, Hongkuan and Zheng, Da and Nisa, Israt and Ioannidis, Vasileios and Song, Xiang and Karypis, George},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {8},
        pages = {1572--1580},
        doi = {10.14778/3529337.3529342},
        url = {https://doi.org/10.14778/3529337.3529342},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 21 of 21 citing papers.

Rank Citing Paper Year Venue Pagerank
3,017 Zebra: When Temporal Graph Neural Networks Meet Temporal Personalized PageRank 2023 VLDB 7.7471344e-05
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
4,993 DGC: Training Dynamic Graphs with Spatio-Temporal Non-Uniformity using Graph Partitioning by Chunks 2023 SIGMOD 6.32357e-05
5,051 Decoupled Graph Neural Networks for Large Dynamic Graphs 2023 VLDB 6.2961385e-05
5,677 SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning 2023 VLDB 6.041013e-05
6,109 GENTI: GPU-powered Walk-based Subgraph Extraction for Scalable Representation Learning on Dynamic Graphs 2024 VLDB 5.8845577e-05
6,324 EARLY: Efficient and Reliable Graph Neural Network for Dynamic Graphs 2023 SIGMOD 5.8137796e-05
6,826 SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement 2024 SIGMOD 5.6700316e-05
8,623 D3-GNN: Dynamic Distributed Dataflow for Streaming Graph Neural Networks 2024 VLDB 5.3009314e-05
9,232 PipeTGL: (Near) Zero Bubble Memory-based Temporal Graph Neural Network Training via Pipeline Optimization 2025 VLDB 5.2056825e-05
9,234 Effective and Efficient Distributed Temporal Graph Learning through Hotspot Memory Sharing 2025 VLDB 5.2056825e-05
9,528 Temporal SIR-GN: Efficient and Effective Structural Representation Learning for Temporal Graphs 2023 VLDB 5.1656406e-05
9,900 Scalable Graph Convolutional Network Training on Distributed-Memory Systems 2023 VLDB 5.1116429e-05
10,043 The Image Calculator: 10x Faster Image-AI Inference by Replacing JPEG with Self-designing Storage Format 2024 SIGMOD 5.0921006e-05
10,535 SWIFT: Enabling Large-Scale Temporal Graph Learning on a Single Machine 2026 SIGMOD 4.9793485e-05
10,779 PRISM: A Training System to Unlock the Potential of Temporal Graph Learning Through Staleness Avoidance 2026 VLDB 4.9793485e-05
11,066 Understanding Evolving Graph Structures for Large Discrete-Time Dynamic Graph Representation 2026 VLDB 4.9793485e-05
11,198 SWASH: A Flexible Communication Framework with Sliding Window-Based Cache Sharing for Scalable DGNN Training 2025 SIGMOD 4.9793485e-05
11,314 When Speed meets Accuracy: an Efficient and Effective Graph Model for Temporal Link Prediction 2025 VLDB 4.9793485e-05
11,459 Towards Ideal Temporal Graph Neural Networks: Evaluations and Conclusions after 10,000 GPU Hours 2025 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

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

Rank Cited Paper Year Venue Pagerank
881 APAN: Asynchronous Propagation Attention Network for Real-time Temporal Graph Embedding 2021 SIGMOD 0.00013278822
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Semantically Similar Papers

# Overall Rank Paper Year Venue
1 4,826 Accelerating Sampling and Aggregation Operations in GNN Frameworks with GPU Initiated Direct Storage Accesses 2024 VLDB
2 9,234 Effective and Efficient Distributed Temporal Graph Learning through Hotspot Memory Sharing 2025 VLDB
3 2,596 Scalable and Efficient Full-Graph GNN Training for Large Graphs 2023 SIGMOD
4 1,033 AGL: A Scalable System for Industrial-purpose Graph Machine Learning 2020 VLDB
5 10,706 Efficient GNN Training on Giant Graphs with Collective Batching and Scheduling 2026 VLDB
6 10,535 SWIFT: Enabling Large-Scale Temporal Graph Learning on a Single Machine 2026 SIGMOD
7 9,232 PipeTGL: (Near) Zero Bubble Memory-based Temporal Graph Neural Network Training via Pipeline Optimization 2025 VLDB
8 4,764 ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs 2024 VLDB
9 6,826 SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement 2024 SIGMOD
10 11,459 Towards Ideal Temporal Graph Neural Networks: Evaluations and Conclusions after 10,000 GPU Hours 2025 VLDB