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FPGA-Based Dynamically Reconfigurable SQL Query Processing

Authors:

Andreas Becher,

Christopher Dennl,

Klaus Meyer-Wegener,

Ute Schürfeld,

Jörg-Stephan Vogt,

Helmut WeberAuthors Info & Claims

ACM Transactions on Reconfigurable Technology and Systems (TRETS), Volume 9, Issue 4

Article No.: 25, Pages 1 - 24

https://doi.org/10.1145/2845087

Published: 22 August 2016 Publication History

Abstract

In this article, we propose an FPGA-based SQL query processing approach exploiting the capabilities of partial dynamic reconfiguration of modern FPGAs. After the analysis of an incoming query, a query-specific hardware processing unit is generated on the fly and loaded on the FPGA for immediate query execution. For each query, a specialized hardware accelerator pipeline is composed and configured on the FPGA from a set of presynthesized hardware modules. These partially reconfigurable hardware modules are gathered in a library covering all major SQL operations like restrictions and aggregations, as well as more complex operations such as joins and sorts. Moreover, this holistic query processing approach in hardware supports different data processing strategies including row- as column-wise data processing in order to optimize data communication and processing. This article gives an overview of the proposed query processing methodology and the corresponding library of modules. Additionally, a performance analysis is introduced that is able to estimate the processing time of a query for different processing strategies and different communication and processing architecture configurations. With the help of this performance analysis, architectural bottlenecks may be exposed and future optimized architectures, besides the two prototypes presented here, may be determined.

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Cited By

Broneske DBurtsev VDrewes AGurumurthy BPionteck TSaake G(2025)ADAMANT: Hardware-Accelerated Query Processing Made EasyScalable Data Management for Future Hardware10.1007/978-3-031-74097-8_1(1-38)Online publication date: 24-Jan-2025
https://doi.org/10.1007/978-3-031-74097-8_1
Lu ANarendra Agrawal JFang Z(2024)SQL2FPGA: Automated Acceleration of SQL Query Processing on Modern CPU-FPGA PlatformsACM Transactions on Reconfigurable Technology and Systems10.1145/367484317:3(1-28)Online publication date: 2-Jul-2024
https://dl.acm.org/doi/10.1145/3674843
Drewes ABurtsev VGurumurthy BWilhelm MBroneske DSaake GPionteck T(2024)An Architectural Template for FPGA Overlays Targeting Data Flow Applications2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)10.1109/IPDPSW63119.2024.00042(162-168)Online publication date: 27-May-2024
https://doi.org/10.1109/IPDPSW63119.2024.00042
Show More Cited By

Index Terms

FPGA-Based Dynamically Reconfigurable SQL Query Processing

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Information

Published In

cover image ACM Transactions on Reconfigurable Technology and Systems

ACM Transactions on Reconfigurable Technology and Systems Volume 9, Issue 4

Regular Papers and Special Section on Field Programmable Gate Arrays (FPGA) 2015

September 2016

161 pages

ISSN:1936-7406

EISSN:1936-7414

DOI:10.1145/2984740

Editor:
Steve Wilton
Department of Electrical and Computer Engineering/University of British Columbia/Kaiser 4112, 5500-2332 Main Mall/Vancouver, BC V6T 1Z4 Canada

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Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 August 2016

Accepted: 01 November 2015

Revised: 01 September 2015

Received: 01 May 2015

Published in TRETS Volume 9, Issue 4

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Cited By

Broneske DBurtsev VDrewes AGurumurthy BPionteck TSaake G(2025)ADAMANT: Hardware-Accelerated Query Processing Made EasyScalable Data Management for Future Hardware10.1007/978-3-031-74097-8_1(1-38)Online publication date: 24-Jan-2025
https://doi.org/10.1007/978-3-031-74097-8_1
Lu ANarendra Agrawal JFang Z(2024)SQL2FPGA: Automated Acceleration of SQL Query Processing on Modern CPU-FPGA PlatformsACM Transactions on Reconfigurable Technology and Systems10.1145/367484317:3(1-28)Online publication date: 2-Jul-2024
https://dl.acm.org/doi/10.1145/3674843
Drewes ABurtsev VGurumurthy BWilhelm MBroneske DSaake GPionteck T(2024)An Architectural Template for FPGA Overlays Targeting Data Flow Applications2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)10.1109/IPDPSW63119.2024.00042(162-168)Online publication date: 27-May-2024
https://doi.org/10.1109/IPDPSW63119.2024.00042
Hahn TSchüll DWildermann STeich J(2024)ABACUS: ASIP-Based Avro Schema-Customizable Parser Acceleration on FPGAs2024 27th International Symposium on Design & Diagnostics of Electronic Circuits & Systems (DDECS)10.1109/DDECS60919.2024.10508904(79-85)Online publication date: 3-Apr-2024
https://doi.org/10.1109/DDECS60919.2024.10508904
Jiang KWang XWang SXue HYu FLi R(2024)A Generalized Design for Database Heterogeneous Query Acceleration Based on FPGA2024 China Automation Congress (CAC)10.1109/CAC63892.2024.10864689(1419-1426)Online publication date: 1-Nov-2024
https://doi.org/10.1109/CAC63892.2024.10864689
Lohmann STutsch D(2023)The Doubly Linked Tree of Singly Linked Rings: Providing Hard Real-Time Database Operations on an FPGAComputers10.3390/computers1301000813:1(8)Online publication date: 24-Dec-2023
https://doi.org/10.3390/computers13010008
Gurumurthy BBroneske DDurand GPionteck TSaake G(2023)ADAMANT: A Query Executor with Plug-In Interfaces for Easy Co-processor Integration2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00093(1153-1166)Online publication date: Apr-2023
https://doi.org/10.1109/ICDE55515.2023.00093
Lu AFang Z(2023)SQL2FPGA: Automatic Acceleration of SQL Query Processing on Modern CPU-FPGA Platforms2023 IEEE 31st Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)10.1109/FCCM57271.2023.00028(184-194)Online publication date: May-2023
https://doi.org/10.1109/FCCM57271.2023.00028
Burtsev VWilhelm MDrewes AGurumurthy BBroneske DPionteck TSaake G(2023)FPGA-Integrated Bag of Little Bootstraps Accelerator for Approximate Database Query ProcessingApplied Reconfigurable Computing. Architectures, Tools, and Applications10.1007/978-3-031-42921-7_8(115-130)Online publication date: 16-Sep-2023
https://doi.org/10.1007/978-3-031-42921-7_8
Zhan JJiang WLi YWu JZhu JYu J(2022)Accelerating Queries of Big Data Systems by Storage-Side CPU-FPGA Co-DesignIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2021.310074341:7(2128-2141)Online publication date: Jul-2022
https://doi.org/10.1109/TCAD.2021.3100743
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