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Accelerating Large Table Scan Using Processing-In-Memory Technology

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Bibliographic Details
Title: Accelerating Large Table Scan Using Processing-In-Memory Technology
Authors: Alexander Baumstark, Muhammad Attahir Jibril, Kai-Uwe Sattler
Source: Datenbank-Spektrum. 23:199-209
Publisher Information: Springer Science and Business Media LLC, 2023.
Publication Year: 2023
Subject Terms: 0103 physical sciences, UPMEM||Processing-In-Memory||In-Memory Database, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 01 natural sciences
Description: Today’s systems are capable of storing large amounts of data in main memory. Particularly, in-memory DBMSs benefit from this development. However, the processing of data from the main memory necessarily has to run via the CPU. This creates a bottleneck, which affects the possible performance of the DBMS. Processing-In-Memory (PIM) is a paradigm to overcome this problem, which was not available in commercial systems for a long time. With the availability of UPMEM, a commercial product is finally available that provides PIM technology in hardware. In this work, we focus on the acceleration of the table scan, a fundamental database query operation. We show and investigate an approach that can be used to optimize this operation by using PIM. We evaluate the PIM scan in terms of parallelism and execution time in benchmarks with different table sizes and compare it to a traditional CPU-based table scan. The result is a PIM table scan that outperforms the CPU-based scan significantly.
Document Type: Article
Other literature type
Language: English
ISSN: 1610-1995
1618-2162
DOI: 10.1007/s13222-023-00456-z
DOI: 10.18420/btw2023-51
Rights: CC BY
Accession Number: edsair.doi.dedup.....ccbadcd439ac3b460ea46d1786d4fc3a
Database: OpenAIRE
Description
Abstract:Today’s systems are capable of storing large amounts of data in main memory. Particularly, in-memory DBMSs benefit from this development. However, the processing of data from the main memory necessarily has to run via the CPU. This creates a bottleneck, which affects the possible performance of the DBMS. Processing-In-Memory (PIM) is a paradigm to overcome this problem, which was not available in commercial systems for a long time. With the availability of UPMEM, a commercial product is finally available that provides PIM technology in hardware. In this work, we focus on the acceleration of the table scan, a fundamental database query operation. We show and investigate an approach that can be used to optimize this operation by using PIM. We evaluate the PIM scan in terms of parallelism and execution time in benchmarks with different table sizes and compare it to a traditional CPU-based table scan. The result is a PIM table scan that outperforms the CPU-based scan significantly.
ISSN:16101995
16182162
DOI:10.1007/s13222-023-00456-z