Efficient Load-Balanced Butterfly Counting on GPU
Summary: G-BFC, a GPU-based butterfly counting approach for large bipartite graphs, unlocks the serial region with shared memory. Adaptive load balancing and wedge-reduction preprocessing tackle workload imbalance and wedge traversal, delivering up to 19.8x speedup across eleven real datasets. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Qingyu Xu (Renmin University of China)
- 2. Feng Zhang (Renmin University of China)
- 3. Zhiming Yao (Renmin University of China)
- 4. Lv Lu (Renmin University of China)
- 5. Xiaoyong Du (Renmin University of China)
- 6. Dong Deng (Rutgers University–New Brunswick)
- 7. Bingsheng He (National University of Singapore)
BibTeX Citation
@article{xu_vldb22,
title = {{Efficient Load-Balanced Butterfly Counting on GPU}},
author = {Xu, Qingyu and Zhang, Feng and Yao, Zhiming and Lu, Lv and Du, Xiaoyong and Deng, Dong and He, Bingsheng},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {11},
pages = {2450--2462},
doi = {10.14778/3551793.3551806},
url = {https://doi.org/10.14778/3551793.3551806},
year = {2022}
}Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,890 | Efficient Temporal Butterfly Counting and Enumeration on Temporal Bipartite Graphs | 2024 | VLDB | 6.9442248e-05 |
| 7,602 | Scalable Approximate Butterfly and Bi-triangle Counting for Large Bipartite Networks | 2023 | SIGMOD | 5.4868396e-05 |
| 9,735 | Common Neighborhood Estimation over Bipartite Graphs under Local Differential Privacy | 2024 | SIGMOD | 5.1349531e-05 |
| 10,568 | Fast Optimal Group Steiner Tree Search using GPUs | 2026 | SIGMOD | 4.9793485e-05 |
| 10,634 | Efficient and Effective Biclique Counting with Local Differential Privacy | 2026 | SIGMOD | 4.9793485e-05 |
| 10,871 | Efficient GPU-Accelerated Adaptive Minimum Cost Seed Selection | 2026 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 131 | Discovering Large Dense Subgraphs in Massive Graphs | 2005 | VLDB | 0.00030242586 |
| 766 | Maximum Biclique Search at Billion Scale | 2020 | VLDB | 0.00014118259 |
| 834 | K-Core Decomposition of Large Networks on a Single PC | 2016 | VLDB | 0.00013583208 |
| 1,222 | Vertex Priority Based Butterfly Counting for Large-scale Bipartite Networks | 2019 | VLDB | 0.00011463714 |
| 2,469 | Pangolin: An Efficient and Flexible Graph Mining System on CPU and GPU | 2020 | VLDB | 8.4165523e-05 |
| 3,314 | Accelerating Triangle Counting on GPU | 2021 | SIGMOD | 7.4380767e-05 |
| 4,405 | Efficient Document Analytics on Compressed Data: Method, Challenges, Algorithms, Insights | 2018 | VLDB | 6.6128353e-05 |
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| # | Overall Rank | Paper | Year | Venue |
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| 1 | 10,746 | gMatch: Fine-Grained and Hardware-Efficient Subgraph Matching on GPUs | 2026 | VLDB |
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| 6 | 10,102 | Efficient Historical Butterfly Counting in Large Temporal Bipartite Networks via Graph Structure-aware Index | 2025 | VLDB |
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| 8 | 5,558 | I/O-Efficient Butterfly Counting at Scale | 2023 | SIGMOD |
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