GPU-based Graph Traversal on Compressed Graphs
Summary: GPU-based graph traversal on compressed graphs enables processing graphs larger than device memory. Introduces Two-Phase Traversal and Task-Stealing to mitigate SIMT divergence and workload imbalance, plus Warp-centric Decoding and Residual Segmentation for power-law graphs, achieving 2x–18x compression with competitive efficiency. (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_sigmod19,
title = {{GPU-based Graph Traversal on Compressed Graphs}},
author = {Sha, Mo and Li, Yuchen and Tan, Kian-Lee},
series = {{SIGMOD} '19},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3299869.3319871},
url = {https://dl.acm.org/doi/10.1145/3299869.3319871},
year = {2019}
}
Incoming Citations (Sorted by Pagerank)
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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 |
|---|---|---|---|---|
| 1,511 | Speedup Graph Processing by Graph Ordering | 2016 | SIGMOD | 0.00010538011 |
| 2,874 | iBFS: Concurrent Breadth-First Search on GPUs | 2016 | SIGMOD | 8.0094569e-05 |
| 3,303 | A Distributed Multi-GPU System for Fast Graph Processing | 2018 | VLDB | 7.5405596e-05 |
| 3,740 | GTS: A Fast and Scalable Graph Processing Method based on Streaming Topology to GPUs | 2016 | SIGMOD | 7.1593902e-05 |
| 4,088 | Fast Sparse Matrix-Vector Multiplication on GPUs: Implications for Graph Mining | 2011 | VLDB | 6.912485e-05 |
| 4,171 | Accelerating Dynamic Graph Analytics on GPUs | 2018 | VLDB | 6.8537202e-05 |
| 5,250 | Parallel Personalized PageRank on Dynamic Graphs | 2018 | VLDB | 6.2992176e-05 |
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