Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/1739041.1739137acmotherconferencesArticle/Chapter ViewAbstractPublication PagesedbtConference Proceedingsconference-collections
research-article

FPGAs: a new point in the database design space

Published: 22 March 2010 Publication History

Abstract

In line with the insight that "one size" of databases will not fit all application needs [19] the database community is currently exploring various alternatives to commodity, CPU-based system designs. One particular candidate in this trend are field-programmable gate arrays (FPGAs), programmable chips that allow tailor-made hardware designs optimized for specific systems, applications, or even user queries.
With a focus on database use, this tutorial introduces into FPGA technology, demonstrates its potential, but also pinpoints some challenges that need to be addressed before FPGA-accelerated database systems can go mainstream. The goal of this tutorial is to develop an intuition of an FPGA development cycle, receive guidelines for a "good" FPGA design, but also learn the limitations that hardware-implemented database processing faces. Our more high-level ambition is to spur a broader interest in database processing on novel hardware technology.

References

[1]
Zachary K. Baker and Viktor K. Prasanna. Efficient Hardware Data Mining with the Apriori Algorithm on FPGAs. In Proc. of the 13th Symposium on Field-Programmable Custom Computing Machines (FCCM), Napa, CA, USA, April 2005.
[2]
Nagender Bandi, Ahmed Metwally, Divyakant Agrawal, and Amr El Abbadi. Data Stream Algorithms using Associative Memories. In Proc. of the ACM SIGMOD Int'l Conference on Management of Data, Beijing, China, June 2007.
[3]
Nagender Bandi, Chengyu Sun, Divyakant Agrawal, and Amr El Abbadi. Processing Spacial Data Using Graphics Processors. In Proc. of the Int'l Conference on Very Large Databases (VLDB), Toronto, ON, Canada, 2004.
[4]
Jatin Chhugani, Anthony D. Nguyen, Victor W. Lee, William Macy, Mostafa Hagog, Yen-Kuang Chen, Akram Baransi, Sanjeev Kumar, and Pradeep Dubey. Efficient Implementation of Sorting on Multi-Core SIMD CPU architecture. Proc. of the VLDB Endowment, 1(2), 2008.
[5]
Netezza Corp. TwinFin#8482;. http://www.netezza.com/.
[6]
Jeffrey Dean and Sanjay Ghemawat. MapReduce: Simplified Data Processing on Large Clusters. In 6th Symposium on Operating System Design and Implementation, San Francisco, CA, USA, December 2004.
[7]
Buğra Gedik, Rajesh R. Bordawekar, and Philip S. Yu. CellSort: High Performance Sorting on the Cell Processor. In Int'l Conference on Very Large Databases (VLDB), Vienna, Austria, September 2007.
[8]
Buğra Gedik, Philip S. Yu, and Rajesh Bordawekar. Executing Stream Joins on the Cell Processor. In Proc. of the Int'l Conference on Very Large Databases (VLDB), Vienna, Austria, 2007.
[9]
Brian T. Gold, Anastassia Ailamaki, Larry Huston, and Babak Falsafi. Accelerating Database Operations Using a Network Processor. In Workshop on Data Management on New Hardware (DaMoN), Baltimore, MD, USA, June 2005.
[10]
Naga Govindaraju, Jim Gray, Ritesh Kumar, and Dinesh Manocha. GPUTeraSort: High Performance Graphics Co-processor Sorting for Large Database Management. In Proc. of the ACM SIGMOD Int'l Conference on Management of Data, Chicago, IL, USA, June 2006.
[11]
Naga K. Govindaraju, Brandon Lloyd, Wei Wang, Ming Lin, and Dinesh Manocha. Fast Computation of Database Operations using Graphics Processors. In Proc. of the ACM SIGMOD Int'l Conference on Management of Data, Paris, France, June 2004.
[12]
Bingsheng He, Ke Yang, Rui Fang, Mian Lu, Naga K. Govindaraju, Qiong Luo, and Pedro V. Sander. Relational Joins on Graphics Processors. In Proc. of the ACM SIGMOD Int'l Conference on Management of Data, Vancouver, BC, Canada, June 2008.
[13]
XtremeData Inc. dbX. http://www.xtremedatainc.com/.
[14]
Kickfire. Analytic Appliance. http://www.kickfire.com.
[15]
H. T. Kung and Charles E. Leiserson. Systolic Arrays (for VLSI). In Sparse Matrix Proceedings, Knoxville, TN, USA, November 1978.
[16]
MonetDB. http://monetdb.cwi.nl/.
[17]
Rene Mueller, Jens Teubner, and Gustavo Alonso. Data Processing on FPGAs. Proc. of the VLDB Endowment, 2(1), August 2009.
[18]
Rene Mueller, Jens Teubner, and Gustavo Alonso. Streams on Wires---A Query Compiler for FPGAs. Proc. of the VLDB Endowment, 2(1), August 2009.
[19]
Michael Stonebraker and Uğur Çetintemel. "One Size Fits All": An Idea Whose Time Has Come and Gone. In Proc. of the 21st Int'l Conference on Data Engineering (ICDE), Tokyo, Japan, April 2005.
[20]
Jens Teubner, Rene Mueller, and Gustavo Alonso. FPGA Acceleration for the Frequent Item Problem. In Proc. of the 26th Int'l Conference on Data Engineering (ICDE), Long Beach, CA, USA, March 2010.
[21]
Dina Thomas, Rajesh Bordawekar, Charu C. Aggarwal, and Philip S. Yu. On Efficient Query Processing of Stream Counts on the Cell Processor. In Proc. of the 25th Int'l Conference on Data Engineering (ICDE), Shanghai, China, March 2009.
[22]
Thomas Willhalm, Nicolae Popovici, Yazan Boshmaf, Hasso Plattner, Alexander Zeier, and Jan Schaffner. SIMD-Scan: Ultra Fast in-Memory Table Scan using on-Chip Vector Processing Units. Proc. of the VLDB Endowment, 2(1), August 2009.

Cited By

View all
  • (2024)SIMDified Data Processing - Foundations, Abstraction, and Advanced TechniquesCompanion of the 2024 International Conference on Management of Data10.1145/3626246.3654694(613-621)Online publication date: 9-Jun-2024
  • (2022)Energy-Efficient Database Systems: A Systematic SurveyACM Computing Surveys10.1145/353822555:6(1-53)Online publication date: 7-Dec-2022
  • (2019)In-memory database acceleration on FPGAs: a surveyThe VLDB Journal10.1007/s00778-019-00581-wOnline publication date: 26-Oct-2019
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences
EDBT '10: Proceedings of the 13th International Conference on Extending Database Technology
March 2010
741 pages
ISBN:9781605589459
DOI:10.1145/1739041
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 ACM 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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 March 2010

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. FPGA
  2. VLSI
  3. data processing
  4. hardware acceleration

Qualifiers

  • Research-article

Funding Sources

Conference

EDBT/ICDT '10
EDBT/ICDT '10: EDBT/ICDT '10 joint conference
March 22 - 26, 2010
Lausanne, Switzerland

Acceptance Rates

Overall Acceptance Rate 7 of 10 submissions, 70%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)3
  • Downloads (Last 6 weeks)0
Reflects downloads up to 20 Nov 2024

Other Metrics

Citations

Cited By

View all
  • (2024)SIMDified Data Processing - Foundations, Abstraction, and Advanced TechniquesCompanion of the 2024 International Conference on Management of Data10.1145/3626246.3654694(613-621)Online publication date: 9-Jun-2024
  • (2022)Energy-Efficient Database Systems: A Systematic SurveyACM Computing Surveys10.1145/353822555:6(1-53)Online publication date: 7-Dec-2022
  • (2019)In-memory database acceleration on FPGAs: a surveyThe VLDB Journal10.1007/s00778-019-00581-wOnline publication date: 26-Oct-2019
  • (2018)Hardware-aided update acceleration in a hybrid Semantic Web database systemThe Journal of Supercomputing10.1007/s11227-018-2462-yOnline publication date: 20-Jun-2018
  • (2017)A many-core architecture for in-memory data processingProceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture10.1145/3123939.3123985(245-258)Online publication date: 14-Oct-2017
  • (2017)Hardware Accelerated Application Integration ProcessingProceedings of the 11th ACM International Conference on Distributed and Event-based Systems10.1145/3093742.3093911(215-226)Online publication date: 8-Jun-2017
  • (2017)SiliconDBProceedings of the 13th International Workshop on Data Management on New Hardware10.1145/3076113.3076124(1-4)Online publication date: 14-May-2017
  • (2017)Search & Update Optimization of a B $$^+$$ Tree in a Hardware Aided Semantic Web Database SystemProceedings of the 7th International Conference on Emerging Databases10.1007/978-981-10-6520-0_18(172-182)Online publication date: 14-Oct-2017
  • (2016)An FPGA approach for fast bitmap indexingIEICE Electronics Express10.1587/elex.13.2016000613:4(20160006-20160006)Online publication date: 2016
  • (2016)Symbiote Coprocessor Unit—A Streaming Coprocessor for Data Stream AccelerationIEEE Transactions on Very Large Scale Integration (VLSI) Systems10.1109/TVLSI.2015.243206324:3(813-826)Online publication date: 1-Mar-2016
  • Show More Cited By

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media