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Efficient Top-K Query Processing on Massively Parallel Hardware

Summary: GPU-based top-k algorithms for massively parallel data analytics, including a novel bitonic top-k with up to 15x speedups over sort for k ≤ 256. A cost model predicts relative performance across algorithms and matches measurements on modern GPUs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5517
Venue
SIGMOD
Year
2018
Pagerank
5.6313494e-05
Overall Rank
7,370 | 49.44%
DOI
10.1145/3183713.3183735

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{shanbhag_sigmod18,
        title = {{Efficient Top-K Query Processing on Massively Parallel Hardware}},
        author = {Shanbhag, Anil and Pirk, Holger and Madden, Samuel},
        series = {{SIGMOD} '18},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3183713.3183735},
        url = {https://dl.acm.org/doi/10.1145/3183713.3183735},
        year = {2018}
}

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