PipeTGL: (Near) Zero Bubble Memory-based Temporal Graph Neural Network Training via Pipeline Optimization

Summary: PipeTGL: pipeline-parallel training for memory-based temporal GNNs that models inter-minibatch memory dependencies via a runtime DAG and uses fine-grained scheduling, operation reordering, and targeted communication to honor chronological memory constraints. Achieves near-zero pipeline bubbles, reduces GPU idle/communication overhead, and delivers 1.27–4.74× speedups with improved multi-GPU training accuracy. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: h35ab6a250ab6fd3d
Venue: VLDB
Year: 2025
Pagerank: 5.2056825e-05
Overall Rank: 9,232 | 37.93%
DOI: 10.14778/3742728.3742760

Incoming Non-self Citations Over Time

Authors

1. Jun Liu (Huazhong University of Science and Technology)
2. Bingqian Du (Huazhong University of Science and Technology)
3. Ziyue Luo (Ohio State University)
4. Sitian Lu (Huazhong University of Science and Technology)
5. Qiankun Zhang (Huazhong University of Science and Technology)
6. Hai Jin (Huazhong University of Science and Technology)

BibTeX Citation

@article{liu_vldb25,
        title = {{PipeTGL: (Near) Zero Bubble Memory-based Temporal Graph Neural Network Training via Pipeline Optimization}},
        author = {Liu, Jun and Du, Bingqian and Luo, Ziyue and Lu, Sitian and Zhang, Qiankun and Jin, Hai},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {8},
        pages = {2722--2734},
        doi = {10.14778/3742728.3742760},
        url = {https://doi.org/10.14778/3742728.3742760},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,779	PRISM: A Training System to Unlock the Potential of Temporal Graph Learning Through Staleness Avoidance	2026	VLDB	4.9793485e-05

Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 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
1,364	TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs	2022	VLDB	0.00010914152
3,017	Zebra: When Temporal Graph Neural Networks Meet Temporal Personalized PageRank	2023	VLDB	7.7471344e-05
3,399	Orca: Scalable Temporal Graph Neural Network Training with Theoretical Guarantees	2023	SIGMOD	7.3349076e-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

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