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Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture

Summary: GPU-oriented GCN training bypasses CPU feature gathering by using GPU zero-copy access to host-resident sparse features. Address alignment and asynchronous transfer/execution improve PCIe efficiency, yielding 65–92% faster multi-GPU training on billion-edge graphs. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
hc4f368cd563c6fe6
Venue
VLDB
Year
2021
Pagerank
0.000114497
Overall Rank
1,224 | 91.78%
DOI
10.14778/3476249.3476264

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{min_vldb21,
        title = {{Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture}},
        author = {Min, Seung Won and Wu, Kun and Huang, Sitao and Hidayetoğlu, Mert and Xiong, Jinjun and Ebrahimi, Eiman and Chen, Deming and Hwu, Wen-mei},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {11},
        pages = {2087--2100},
        doi = {10.14778/3476249.3476264},
        url = {https://doi.org/10.14778/3476249.3476264},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 15 of 15 citing papers.

Rank Citing Paper Year Venue Pagerank
1,134 SANCUS: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks 2022 VLDB 0.00011893521
2,279 NeutronStar: Distributed GNN Training with Hybrid Dependency Management 2022 SIGMOD 8.7062637e-05
2,506 DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with the GPU 2023 SIGMOD 8.3774747e-05
2,863 Ginex: SSD-enabled Billion-scale Graph Neural Network Training on a Single Machine via Provably Optimal In-memory Caching 2022 VLDB 7.9301802e-05
4,764 ETC: Efficient Training of Temporal Graph Neural Networks over Large-scale Dynamic Graphs 2024 VLDB 6.4276208e-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
6,793 XGNN: Boosting Multi-GPU GNN Training via Global GNN Memory Store 2024 VLDB 5.6810336e-05
6,826 SIMPLE: Efficient Temporal Graph Neural Network Training at Scale with Dynamic Data Placement 2024 SIGMOD 5.6700316e-05
6,852 OUTRE: An OUT-of-core De-REdundancy GNN Training Framework for Massive Graphs within A Single Machine 2024 VLDB 5.6647613e-05
6,924 HongTu: Scalable Full-Graph GNN Training on Multiple GPUs 2023 SIGMOD 5.6426299e-05
8,400 TOD: GPU-accelerated Outlier Detection via Tensor Operations 2023 VLDB 5.3395906e-05
9,900 Scalable Graph Convolutional Network Training on Distributed-Memory Systems 2023 VLDB 5.1116429e-05
11,338 Efficient Graph Data Access for Out-of-Memory GPU Streaming Graph Processing 2025 VLDB 4.9793485e-05
11,576 TIGER: Training Inductive Graph Neural Network for Large-scale Knowledge Graph Reasoning 2024 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank Cited Paper Year Venue Pagerank
2,068 Traversing Large Graphs on GPUs with Unified Memory 2020 VLDB 9.0920811e-05
5,521 EMOGI: Efficient Memory-access for Out-of-memory Graph-traversal in GPUs 2021 VLDB 6.0959947e-05
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# Overall Rank Paper Year Venue
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4 3,752 G3: When Graph Neural Networks Meet Parallel Graph Processing Systems on GPUs 2020 VLDB
5 1,772 ByteGNN: Efficient Graph Neural Network Training at Large Scale 2022 VLDB
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7 4,207 GPU-based Graph Traversal on Compressed Graphs 2019 SIGMOD
8 2,596 Scalable and Efficient Full-Graph GNN Training for Large Graphs 2023 SIGMOD
9 4,826 Accelerating Sampling and Aggregation Operations in GNN Frameworks with GPU Initiated Direct Storage Accesses 2024 VLDB
10 9,900 Scalable Graph Convolutional Network Training on Distributed-Memory Systems 2023 VLDB