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Fast and Approximate Stream Mining of Quantiles and Frequencies Using Graphics Processors

Summary: GPU-accelerated, deterministic stream mining of quantiles and frequencies via rasterized sorting for histogram-based epsilon-approx summaries. Co-processor GPU with minimal CPU-GPU data transfer on commodity hardware; supports fixed/variable sliding windows and large streams (>100M values), beating CPU baselines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3732
Venue
SIGMOD
Year
2005
Pagerank
6.3121293e-05
Overall Rank
5,216 | 64.22%
DOI
10.1145/1066157.1066227

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{govindaraju_sigmod05,
        title = {{Fast and Approximate Stream Mining of Quantiles and Frequencies Using Graphics Processors}},
        author = {Govindaraju, Naga K. and Raghuvanshi, Nikunj and Manocha, Dinesh},
        series = {{SIGMOD} '05},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1066157.1066227},
        url = {https://dl.acm.org/doi/10.1145/1066157.1066227},
        year = {2005}
}

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