TurboGraph++: A Scalable and Fast Graph Analytics System
Summary: TurboGraph++ enables scalable external-memory graph analytics in a fixed memory budget, supporting multi-hop neighborhood tasks. Balanced partitioning with three-level parallelism enables Gemini-like performance on Chaos-scale graphs. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Seongyun Ko (Pohang University of Science and Technology)
- 2. Wook-Shin Han (Pohang University of Science and Technology)
BibTeX Citation
@inproceedings{ko_sigmod18,
title = {{TurboGraph++: A Scalable and Fast Graph Analytics System}},
author = {Ko, Seongyun and Han, Wook-Shin},
series = {{SIGMOD} '18},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3183713.3196915},
url = {https://dl.acm.org/doi/10.1145/3183713.3196915},
year = {2018}
}
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