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Processing-in-Memory for Databases: Query Processing and Data Transfer

Authors:

Alexander Baumstark,

Muhammad Attahir Jibril,

Kai-Uwe SattlerAuthors Info & Claims

DaMoN '23: Proceedings of the 19th International Workshop on Data Management on New Hardware

Pages 107 - 111

https://doi.org/10.1145/3592980.3595323

Published: 18 June 2023 Publication History

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Abstract

The Processing-in-Memory (PIM) paradigm promises to accelerate data processing by pushing down computation to memory, reducing the amount of data transfer between memory and CPU, and – in this way – relieving the CPU from processing. Particularly, in in-memory databases memory access becomes a performance bottleneck. Thus, PIM seems to offer an interesting solution for database processing. In this work, we investigate how commercially available PIM technology can be leveraged to accelerate query processing by offloading (parts of) query operators to memory. Furthermore, we show how to address the problem of limited PIM storage capacity by interleaving transfer and computation and present a cost model for the data placement problem.

References

[1]

Alexander Baumstark, Muhammad Attahir Jibril, and Kai-Uwe Sattler. 2023. Accelerating Large Table Scan using Processing-In-Memory Technology. In Datenbanksysteme für Business, Technologie und Web (BTW 2023), 20. Fachtagung des GI-Fachbereichs,Datenbanken und Informationssysteme" (DBIS), 06.-10, März 2023, Dresden, Germany, Proceedings(LNI, Vol. P-331), Birgitta König-Ries, Stefanie Scherzinger, Wolfgang Lehner, and Gottfried Vossen (Eds.). Gesellschaft für Informatik e.V., 797–814. https://doi.org/10.18420/BTW2023-51

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[2]

Alexander Baumstark, Muhammad Attahir Jibril, and Kai-Uwe Sattler. 2023. Adaptive Query Compilation with Processing-in-Memory. In HardBD & Active’23, ICDE Workshops.

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[3]

Juan Gómez-Luna, Izzat El Hajj, Ivan Fernandez, Christina Giannoula, Geraldo F. Oliveira, and Onur Mutlu. 2022. Benchmarking a New Paradigm: Experimental Analysis and Characterization of a Real Processing-in-Memory System. IEEE Access 10 (2022), 52565–52608. https://doi.org/10.1109/ACCESS.2022.3174101

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[4]

Muhammad Attahir Jibril, Alexander Baumstark, Philipp Götze, and Kai-Uwe Sattler. 2021. JIT happens: Transactional Graph Processing in Persistent Memory meets Just-In-Time Compilation. In Proceedings of the 24th International Conference on Extending Database Technology, EDBT 2021, Nicosia, Cyprus, March 23 - 26, 2021, Yannis Velegrakis, Demetris Zeinalipour-Yazti, Panos K. Chrysanthis, and Francesco Guerra (Eds.). OpenProceedings.org, 37–48. https://doi.org/10.5441/002/edbt.2021.05

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Hongbo Kang, Yiwei Zhao, Guy E. Blelloch, Laxman Dhulipala, Yan Gu, Charles McGuffey, and Phillip B. Gibbons. 2022. PIM-tree: A Skew-resistant Index for Processing-in-Memory. Proc. VLDB Endow. 16, 4 (2022), 946–958. https://www.vldb.org/pvldb/vol16/p946-kang.pdf

Digital Library

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UPMEM. 2022. https://www.upmem.com/.

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Cited By

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Lee SLim CChoi JChoi HLee CPark YPark KKim HKim Y(2024)SPID-Join: A Skew-resistant Processing-in-DIMM Join Algorithm Exploiting the Bank- and Rank-level Parallelisms of DIMMsProceedings of the ACM on Management of Data10.1145/36988272:6(1-27)Online publication date: 20-Dec-2024
https://dl.acm.org/doi/10.1145/3698827
Li CZhou ZWang YYang FCao TYang MLiang YSun GTsafrir DMusuvathi MGupta RAbu-Ghazaleh N(2024)PIM-DL: Expanding the Applicability of Commodity DRAM-PIMs for Deep Learning via Algorithm-System Co-OptimizationProceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 210.1145/3620665.3640376(879-896)Online publication date: 27-Apr-2024
https://dl.acm.org/doi/10.1145/3620665.3640376
Berthold ASchmidt LObersteiner AHabich DLehner WSchirmeier H(2024)On-The-Fly Data Distribution to Accelerate Query Processing in Heterogeneous Memory SystemsAdvances in Databases and Information Systems10.1007/978-3-031-70626-4_12(170-183)Online publication date: 1-Sep-2024
https://doi.org/10.1007/978-3-031-70626-4_12

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Information

Published In

DaMoN '23: Proceedings of the 19th International Workshop on Data Management on New Hardware

June 2023

119 pages

ISBN:9798400701917

DOI:10.1145/3592980

Editors:
Norman May
SAP SE, Germany
,
Nesime Tatbul
Intel Labs and MIT, USA

This work is licensed under a Creative Commons Attribution International 4.0 License.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 June 2023

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Research
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SIGMOD/PODS '23

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SIGMOD

SIGMOD/PODS '23: International Conference on Management of Data

June 18 - 23, 2023

WA, Seattle, USA

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DaMoN '23 Paper Acceptance Rate 17 of 23 submissions, 74%;

Overall Acceptance Rate 94 of 127 submissions, 74%

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Cited By

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Lee SLim CChoi JChoi HLee CPark YPark KKim HKim Y(2024)SPID-Join: A Skew-resistant Processing-in-DIMM Join Algorithm Exploiting the Bank- and Rank-level Parallelisms of DIMMsProceedings of the ACM on Management of Data10.1145/36988272:6(1-27)Online publication date: 20-Dec-2024
https://dl.acm.org/doi/10.1145/3698827
Li CZhou ZWang YYang FCao TYang MLiang YSun GTsafrir DMusuvathi MGupta RAbu-Ghazaleh N(2024)PIM-DL: Expanding the Applicability of Commodity DRAM-PIMs for Deep Learning via Algorithm-System Co-OptimizationProceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 210.1145/3620665.3640376(879-896)Online publication date: 27-Apr-2024
https://dl.acm.org/doi/10.1145/3620665.3640376
Berthold ASchmidt LObersteiner AHabich DLehner WSchirmeier H(2024)On-The-Fly Data Distribution to Accelerate Query Processing in Heterogeneous Memory SystemsAdvances in Databases and Information Systems10.1007/978-3-031-70626-4_12(170-183)Online publication date: 1-Sep-2024
https://doi.org/10.1007/978-3-031-70626-4_12

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