Boeschen, Nils ; Binnig, Carsten (2022)
GaccO - A GPU-accelerated OLTP DBMS.
SIGMOD '22: International Conference on Management of Data. Philadelphia, USA (12.06.2022-17.06.2022)
doi: 10.1145/3514221.3517876
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
In this paper, we present GaccO - a main memory DBMS for GPU-accelerated OLTP. For executing OLTP workloads, GaccO implements a novel scheme that splits the execution across the CPU and the GPU. Using such a co-execution scheme GaccO can thus not only efficiently make use of the vectorized execution of the GPU by grouping transactions of the same type into batches, but it can also support databases larger than device memory by leveraging CPU memory in addition to the GPU memory. In our evaluation with TPC-C, we show that GaccO can thus speed-up OLTP workloads by up to 6 times compared to a pure CPU-based OLTP execution.
Typ des Eintrags: | Konferenzveröffentlichung |
---|---|
Erschienen: | 2022 |
Autor(en): | Boeschen, Nils ; Binnig, Carsten |
Art des Eintrags: | Bibliographie |
Titel: | GaccO - A GPU-accelerated OLTP DBMS |
Sprache: | Englisch |
Publikationsjahr: | 11 Juni 2022 |
Verlag: | ACM |
Buchtitel: | SIGMOD'22: Proceedings of the 2022 International Conference on Management of Data |
Veranstaltungstitel: | SIGMOD '22: International Conference on Management of Data |
Veranstaltungsort: | Philadelphia, USA |
Veranstaltungsdatum: | 12.06.2022-17.06.2022 |
DOI: | 10.1145/3514221.3517876 |
Kurzbeschreibung (Abstract): | In this paper, we present GaccO - a main memory DBMS for GPU-accelerated OLTP. For executing OLTP workloads, GaccO implements a novel scheme that splits the execution across the CPU and the GPU. Using such a co-execution scheme GaccO can thus not only efficiently make use of the vectorized execution of the GPU by grouping transactions of the same type into batches, but it can also support databases larger than device memory by leveraging CPU memory in addition to the GPU memory. In our evaluation with TPC-C, we show that GaccO can thus speed-up OLTP workloads by up to 6 times compared to a pure CPU-based OLTP execution. |
Freie Schlagworte: | transaction processing, GPU acceleration, OLTP, systems_maki, systems_funding_52115350 |
Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Data and AI Systems DFG-Sonderforschungsbereiche (inkl. Transregio) DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1053: MAKI – Multi-Mechanismen-Adaption für das künftige Internet |
TU-Projekte: | DFG|SFB1053|SFB1053 TPZ Steinmet |
Hinterlegungsdatum: | 05 Apr 2023 13:09 |
Letzte Änderung: | 24 Jul 2023 09:49 |
PPN: | 509882196 |
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