Beena Gopalakrishnan Nair L, Becher A, Meyer-Wegener K (2020)
Publication Language: English
Publication Type: Conference contribution, Original article
Publication year: 2020
Publisher: ACM Digital Library
Pages Range: 1-3
Conference Proceedings Title: DaMoN '20: Proceedings of the 16th International Workshop on Data Management on New Hardware
Event location: Portland, Oregon USA
ISBN: 78-1-4503-8024-9/20/06.
Open Access Link: https://dl.acm.org/doi/pdf/10.1145/3399666.3399926
Hardware acceleration of database query processing can be done with the help of FPGAs. In particular, they are partially reconfigurable at runtime, which allows for the adaptation to a variety of queries. Reconfiguration itself, however, takes some time. This paper presents optimizations based on query sequences, which reduce the impact of the reconfigurations. Knowledge of upcoming queries is used to avoid reconfiguration overhead. We evaluate our optimizations with a calibrated model. Improvements in execution time of up to 28% can be obtained even with sequences of only two queries.
APA:
Beena Gopalakrishnan Nair, L., Becher, A., & Meyer-Wegener, K. (2020). The ReProVide Query-Sequence Optimization in a Hardware-Accelerated DBMS. In DaMoN '20: Proceedings of the 16th International Workshop on Data Management on New Hardware (pp. 1-3). Portland, Oregon USA: ACM Digital Library.
MLA:
Beena Gopalakrishnan Nair, Lekshmi, Andreas Becher, and Klaus Meyer-Wegener. "The ReProVide Query-Sequence Optimization in a Hardware-Accelerated DBMS." Proceedings of the 16th International Workshop on Data Management on New Hardware Held with ACM SIGMOD/PODS 2020, Portland, Oregon USA ACM Digital Library, 2020. 1-3.
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