Accelerating Truss Decomposition on Heterogeneous Processors
Summary: Accelerates billion-edge truss decomposition via compacted intermediates, skew-aware triangle enumeration, and data-adaptive peeling/counting. A CPU–GPU co-processing design exploits heterogeneous parallelism, achieving up to 10× speedup over prior methods. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yulin Che (Hong Kong University of Science and Technology)
- 2. Zhuohang Lai (Hong Kong University of Science and Technology)
- 3. Shixuan Sun (National University of Singapore)
- 4. Yue Wang (Shenzhen University)
- 5. Qiong Luo (Hong Kong University of Science and Technology)
BibTeX Citation
@article{che_vldb20,
title = {{Accelerating Truss Decomposition on Heterogeneous Processors}},
author = {Che, Yulin and Lai, Zhuohang and Sun, Shixuan and Wang, Yue and Luo, Qiong},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {10},
pages = {1751--1764},
doi = {10.14778/3401960.3401971},
url = {https://doi.org/10.14778/3401960.3401971},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,315 | Accelerating Triangle Counting on GPU | 2021 | SIGMOD | 7.4345556e-05 |
| 3,611 | Efficient k-Clique Listing: An Edge-Oriented Branching Strategy | 2024 | SIGMOD | 7.1609673e-05 |
| 5,976 | Theoretically and Practically Efficient Parallel Nucleus Decomposition | 2022 | VLDB | 5.9272031e-05 |
| 8,072 | Efficient Star-based Truss Maintenance on Dynamic Graphs | 2023 | SIGMOD | 5.3924812e-05 |
| 9,471 | BYO: A Unified Framework for Benchmarking Large-Scale Graph Containers | 2024 | VLDB | 5.170541e-05 |
| 9,878 | Parallel Algorithms for Hierarchical Nucleus Decomposition | 2024 | SIGMOD | 5.115241e-05 |
| 10,496 | Nucleus Decomposition Revisited: An Efficient Counting-Based Approach | 2026 | SIGMOD | 4.9769913e-05 |
| 10,625 | Accelerating Triangle-Connected Truss Community Search Across Heterogeneous Hardware | 2026 | SIGMOD | 4.9769913e-05 |
| 11,603 | Maximum Balanced (k, epsilon)-Bitruss Detection in Signed Bipartite Graph | 2024 | VLDB | 4.9769913e-05 |
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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 |
|---|---|---|---|---|
| 100 | Truss Decomposition in Massive Networks | 2012 | VLDB | 0.0003396253 |
| 184 | Querying K-Truss Community in Large and Dynamic Graphs | 2014 | SIGMOD | 0.00026097449 |
| 1,092 | Truss-based Community Search: a Truss-equivalence Based Indexing Approach | 2017 | VLDB | 0.00012066667 |
| 1,444 | Local Algorithms for Hierarchical Dense Subgraph Discovery | 2019 | VLDB | 0.00010630508 |
| 2,121 | Fast Hierarchy Construction for Dense Subgraphs | 2017 | VLDB | 9.0060232e-05 |
| 2,288 | Unboundedness and Efficiency of Truss Maintenance in Evolving Graphs | 2019 | SIGMOD | 8.6907426e-05 |
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|---|---|---|---|---|
| 1 | 9,160 | Truss-based Community Search over Streaming Directed Graphs | 2024 | VLDB |
| 2 | 9,485 | Accelerating Core Decomposition in Billion-Scale Hypergraphs | 2025 | SIGMOD |
| 3 | 4,758 | Efficient Cohesive Subgraphs Detection in Parallel | 2014 | SIGMOD |
| 4 | 1,444 | Local Algorithms for Hierarchical Dense Subgraph Discovery | 2019 | VLDB |
| 5 | 4,207 | GPU-based Graph Traversal on Compressed Graphs | 2019 | SIGMOD |
| 6 | 3,315 | Accelerating Triangle Counting on GPU | 2021 | SIGMOD |
| 7 | 10,625 | Accelerating Triangle-Connected Truss Community Search Across Heterogeneous Hardware | 2026 | SIGMOD |
| 8 | 10,816 | Efficient Hyper-truss Decomposition over Hypergraphs | 2026 | VLDB |
| 9 | 100 | Truss Decomposition in Massive Networks | 2012 | VLDB |
| 10 | 8,428 | Truss Decomposition in Hypergraphs | 2025 | VLDB |