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Accelerating Large Table Scan using Processing-In-Memory Technology

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2023

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Gesellschaft für Informatik e.V.

Zusammenfassung

Today’s systems are capable of storing large amounts of data in main memory. In-memoryDBMSs can benefit particularly from this development. However, the processing of the data fromthe main memory necessarily has to run via the CPU. This creates a bottleneck, which affects thepossible performance of the DBMS. The Processing-In-Memory (PIM) technology is a paradigm toovercome this problem, which was not available in commercial systems for a long time. However, withthe availability of UPMEM, a commercial system is finally available that provides PIM technologyin hardware. In this work, the main focus was on the optimization of the table scan, a fundamental,and memory-bound operation. Here a possible approach is shown, which can be used to optimizethis operation by using PIM. This method was then tested for parallelism and execution time inbenchmarks with different table sizes and compared to the usual table scan. The result is a table scanthat outperforms the scan on the usual CPU significantly.

Beschreibung

Baumstark, Alexander; Jibril, Muhammad Attahir; Sattler, Kai-Uwe (2023): Accelerating Large Table Scan using Processing-In-Memory Technology. BTW 2023. DOI: 10.18420/BTW2023-51. Bonn: Gesellschaft für Informatik e.V.. ISBN: 978-3-88579-725-8. pp. 797-814. Dresden, Germany. 06.-10. März 2023

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