Octopus: Efficient Hypergraph Pattern Mining with Practical Processing-in-Memory Architecture
Summary: Octopus is the first full-stack HPM accelerator co-designed for practical UPMEM PIM. Its inter-DPU partitioning/load balancing and intra-DPU asynchronous candidate mining exploit massive parallelism, delivering up to 55.4× speedup over the best CPU/GPU systems. (summarized by gpt-5.6-luna on Jul 26 2026)
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Authors
- 1. Yi Zhang (Huazhong University of Science and Technology)
- 2. Deting Chen (Huazhong University of Science and Technology)
- 3. Yu Huang (Huazhong University of Science and Technology)
- 4. Chaoqiang Liu (Huazhong University of Science and Technology)
- 5. Haifeng Liu (Huazhong University of Science and Technology)
- 6. Jianhui Yue (Michigan Technological University)
- 7. Xiaofei Liao (Huazhong University of Science and Technology)
- 8. Hai Jin (Huazhong University of Science and Technology)
BibTeX Citation
@inproceedings{zhang_sigmod26,
title = {{Octopus: Efficient Hypergraph Pattern Mining with Practical Processing-in-Memory Architecture}},
author = {Zhang, Yi and Chen, Deting and Huang, Yu and Liu, Chaoqiang and Liu, Haifeng and Yue, Jianhui and Liao, Xiaofei and Jin, Hai},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3802094},
url = {https://dl.acm.org/doi/10.1145/3802094},
year = {2026}
}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,480 | Pangolin: An Efficient and Flexible Graph Mining System on CPU and GPU | 2020 | VLDB | 8.387452e-05 |
| 6,031 | Near-Data Processing in Database Systems on Native Computational Storage under HTAP Workloads | 2022 | VLDB | 5.8909681e-05 |
| 6,909 | PimPam: Efficient Graph Pattern Matching on Real Processing-in-Memory Hardware | 2024 | SIGMOD | 5.6336966e-05 |
| 7,122 | Design and Analysis of a Processing-in-DIMM Join Algorithm: A Case Study with UPMEM DIMMs | 2023 | SIGMOD | 5.580601e-05 |
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