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Data-Parallel Query Processing on Non-Uniform Data

Summary: Identifies filter and expansion divergence as key GPU inefficiencies under skewed data and fused pipelines. DogQC balances these effects, improving robustness and delivering up to 4.51× speedups over GPU compilers and 4.54× over CPU systems. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
h27ab2ce52f513b75
Venue
VLDB
Year
2020
Pagerank
6.8948667e-05
Overall Rank
3,961 | 73.37%
DOI
10.14778/3380750.3380758

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Authors

BibTeX Citation

@article{funke_vldb20,
        title = {{Data-Parallel Query Processing on Non-Uniform Data}},
        author = {Funke, Henning and Teubner, Jens},
        journal = {PVLDB},
        series = {{VLDB} '20},
        volume = {13},
        number = {6},
        pages = {884--897},
        doi = {10.14778/3380750.3380758},
        url = {https://doi.org/10.14778/3380750.3380758},
        year = {2020}
}

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