Self-adaptive Graph Traversal on GPUs
Summary: Self-adaptive graph traversal on GPUs; no preprocessing; operates on universal graphs. Proposes Tiled Partition and Resident Tile Stealing for runtime GPU use, plus Sampling-based Reordering for memory efficiency; beats preprocessing-based methods across GPU deployments. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Mo Sha (National University of Singapore)
- 2. Yuchen Li (Singapore Management University)
- 3. Kian-Lee Tan (National University of Singapore)
BibTeX Citation
@inproceedings{sha_sigmod21,
title = {{Self-adaptive Graph Traversal on GPUs}},
author = {Sha, Mo and Li, Yuchen and Tan, Kian-Lee},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3457279},
url = {https://dl.acm.org/doi/10.1145/3448016.3457279},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,650 | gSWORD: GPU-accelerated Sampling for Subgraph Counting | 2024 | SIGMOD | 5.1453267e-05 |
| 10,568 | Fast Optimal Group Steiner Tree Search using GPUs | 2026 | SIGMOD | 4.9793485e-05 |
| 10,809 | GPU-Accelerated eta-threshold Decomposition for Uncertain Graphs | 2026 | VLDB | 4.9793485e-05 |
| 11,053 | Efficient Partition-based Approaches for Diversified Top-k Subgraph Matching | 2026 | VLDB | 4.9793485e-05 |
| 11,056 | Efficient Temporal Edge-Core Maintenance in Streaming Graphs | 2026 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 11 of 11 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 239 | The Ubiquity of Large Graphs and Surprising Challenges of Graph Processing | 2018 | VLDB | 0.000235107 |
| 1,440 | Speedup Graph Processing by Graph Ordering | 2016 | SIGMOD | 0.00010641888 |
| 2,068 | Traversing Large Graphs on GPUs with Unified Memory | 2020 | VLDB | 9.0920811e-05 |
| 2,468 | GPU-Accelerated Subgraph Enumeration on Partitioned Graphs | 2020 | SIGMOD | 8.4178183e-05 |
| 2,789 | iBFS: Concurrent Breadth-First Search on GPUs | 2016 | SIGMOD | 8.0116036e-05 |
| 3,309 | A Distributed Multi-GPU System for Fast Graph Processing | 2018 | VLDB | 7.4409797e-05 |
| 4,207 | GPU-based Graph Traversal on Compressed Graphs | 2019 | SIGMOD | 6.7343908e-05 |
| 4,237 | Accelerating Dynamic Graph Analytics on GPUs | 2018 | VLDB | 6.7107028e-05 |
| 5,300 | Parallel Personalized PageRank on Dynamic Graphs | 2018 | VLDB | 6.1896851e-05 |
| 5,521 | EMOGI: Efficient Memory-access for Out-of-memory Graph-traversal in GPUs | 2021 | VLDB | 6.0959947e-05 |
| 7,716 | Accelerating Exact Constrained Shortest Paths on GPUs | 2021 | VLDB | 5.4683652e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 1,840 | Towards Effective Partition Management for Large Graphs | 2012 | SIGMOD |
| 2 | 3,314 | Accelerating Triangle Counting on GPU | 2021 | SIGMOD |
| 3 | 4,826 | Accelerating Sampling and Aggregation Operations in GNN Frameworks with GPU Initiated Direct Storage Accesses | 2024 | VLDB |
| 4 | 2,468 | GPU-Accelerated Subgraph Enumeration on Partitioned Graphs | 2020 | SIGMOD |
| 5 | 10,882 | Efficient GPU-Accelerated Local Subgraph Counting | 2026 | VLDB |
| 6 | 5,172 | CGgraph: An Ultra-fast Graph Processing System on Modern Commodity CPU-GPU Co-processor | 2024 | VLDB |
| 7 | 4,237 | Accelerating Dynamic Graph Analytics on GPUs | 2018 | VLDB |
| 8 | 5,521 | EMOGI: Efficient Memory-access for Out-of-memory Graph-traversal in GPUs | 2021 | VLDB |
| 9 | 2,068 | Traversing Large Graphs on GPUs with Unified Memory | 2020 | VLDB |
| 10 | 4,207 | GPU-based Graph Traversal on Compressed Graphs | 2019 | SIGMOD |