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doppioDB: A Hardware Accelerated Database

Summary: doppioDB extends MonetDB with hardware UDFs (HUDFs) to accelerate LIKE, REGEXP_LIKE, SKYLINE, and SGD. On Intel Xeon+FPGA with cache-coherent shared memory, HUDFs are schedulable hardware operators enabling seamless integration and workload-adaptive acceleration. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5441
Venue
SIGMOD
Year
2017
Pagerank
5.426661e-05
Overall Rank
8,425 | 42.20%
DOI
10.1145/3035918.3058746

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{sidler_sigmod17,
        title = {{doppioDB: A Hardware Accelerated Database}},
        author = {Sidler, David and István, Zsolt and Owaida, Muhsen and Kara, Kaan and Alonso, Gustavo},
        series = {{SIGMOD} '17},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3035918.3058746},
        url = {https://dl.acm.org/doi/10.1145/3035918.3058746},
        year = {2017}
}

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
8,199 Accelerating Pattern Matching Queries in Hybrid CPU-FPGA Architectures 2017 SIGMOD 5.4686907e-05
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