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dc.contributor.author
Chiosa, Monica
dc.contributor.author
Maschi, Fabio
dc.contributor.author
Müller, Ingo
dc.contributor.author
Alonso, Gustavo
dc.contributor.author
May, Norman
dc.date.accessioned
2022-10-12T12:22:29Z
dc.date.available
2022-08-15T08:25:13Z
dc.date.available
2022-08-15T08:42:19Z
dc.date.available
2022-09-22T06:42:43Z
dc.date.available
2022-10-12T12:22:29Z
dc.date.issued
2022-08
dc.identifier.issn
2150-8097
dc.identifier.other
10.14778/3554821.3554822
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/563725
dc.identifier.doi
10.3929/ethz-b-000563725
dc.description.abstract
With the advent of cloud computing, where computational resources are expensive and data movement needs to be secured and minimized, database management systems need to reconsider their architecture to accommodate such requirements. In this paper, we present our analysis, design and evaluation of an FPGA-based hardware accelerator for offloading compression and encryption for SAP HANA, SAP's Software-as-a-Service (SaaS) in-memory database. Firstly, we identify expensive data-transformation operations in the I/O path. Then we present the design details of a system consisting of compression followed by different types of encryption to accommodate different security levels, and identify which combinations maximize performance. We also analyze the performance benefits of offloading decryption to the FPGA followed by decompression on the CPU. The experimental evaluation using SAP HANA traces shows that analytical engines can benefit from FPGA hardware offloading. The results identify a number of important trade-offs (e.g., the system can accommodate low-latency secured transactions to high-performance use cases or offer lower storage cost by also compressing payloads for less critical use cases), and provide valuable information to researchers and practitioners exploring the nascent space of hardware accelerators for database engines.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Association for Computing Machinery
en_US
dc.rights.uri
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject
FPGA
en_US
dc.title
Hardware Acceleration of Compression and Encryption in SAP HANA
en_US
dc.type
Conference Paper
dc.rights.license
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
dc.date.published
2022-09-29
ethz.journal.title
Proceedings of the VLDB Endowment
ethz.journal.volume
15
en_US
ethz.journal.issue
12
en_US
ethz.journal.abbreviated
Proc. VLDB Endow.
ethz.pages.start
3277
en_US
ethz.pages.end
3291
en_US
ethz.size
15 p. accepted version
en_US
ethz.version.deposit
acceptedVersion
en_US
ethz.event
48th International Conference on Very Large Databases (VLDB 2022)
en_US
ethz.event.location
Sydney, Australia
en_US
ethz.event.date
September 5-9, 2022
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
New York, NY
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02663 - Institut für Computing Platforms / Institute for Computing Platforms::03506 - Alonso, Gustavo / Alonso, Gustavo
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02663 - Institut für Computing Platforms / Institute for Computing Platforms::03506 - Alonso, Gustavo / Alonso, Gustavo
en_US
ethz.date.deposited
2022-08-15T08:25:20Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2022-10-12T12:22:31Z
ethz.rosetta.lastUpdated
2024-02-02T18:41:09Z
ethz.rosetta.versionExported
true
ethz.COinS
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