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International Conference on Algorithms and Architectures for Parallel Processing

ICA3PP 2016: Algorithms and Architectures for Parallel Processing pp 226–233Cite as

Efficiency of GPUs for Relational Database Engine Processing

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10049))

Abstract

Relational database management systems (RDBMS) are still widely required by numerous business applications. Boosting performances without compromising functionalities represents a big challenge. To achieve this goal, we propose to boost an existing RDBMS by making it able to use hardware architectures with high memory bandwidth like GPUs. In this paper we present a solution named CuDB. We compare the performances and energy efficiency of our approach with different GPU ranges. We focus on technical specificities of GPUs which are most relevant for designing high energy efficient solutions for database processing.

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Author information

Authors and Affiliations

  1. Computer Science Department, University of Mons, Rue de Houdain, 9, 7000, Mons, Belgium

    Samuel Cremer, Michel Bagein, Saïd Mahmoudi & Pierre Manneback

Authors
  1. Samuel Cremer
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  2. Michel Bagein
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  3. Saïd Mahmoudi
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  4. Pierre Manneback
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Corresponding authors

Correspondence to Samuel Cremer , Michel Bagein , Saïd Mahmoudi or Pierre Manneback .

Editor information

Editors and Affiliations

  1. Carlos III University of Madrid, Getafe, Spain

    Jesus Carretero

  2. Carlos III University of Madrid, Getafe, Spain

    Javier Garcia-Blas

  3. Mathematical Support for Computers, N. I. Lobachevsky State University of Nizhny Novgorod, Nizhniy Novgorod, Russia

    Victor Gergel

  4. Research Computing Center (RCC), Moscow State University, Moscow, Russia

    Vladimir Voevodin

  5. Research Computing Center (RCC), Moscow State University, Moscow, Russia

    Iosif Meyerov

  6. E.U. Politécnica, Universidad de Extremaddura, Cáceres, Spain

    Juan A. Rico-Gallego

  7. Ingenieria de Sistemas Informáticos, Universidad de Extremaddura, Cáceres, Spain

    Juan C. Díaz-Martín

  8. Universitat Politécnica de València, Valencia, Spain

    Pedro Alonso

  9. Distributed and Parallel Systems Group, Institute for Computer Science, Innsbruck, Austria

    Juan Durillo

  10. Carlos III University of Madrid, Getafe, Spain

    José Daniel Garcia Sánchez

  11. UCD School of Computer Science, University College Dublin, Dublin, Ireland

    Alexey L. Lastovetsky

  12. University of Calabria, Rende (CS), Italy

    Fabrizio Marozzo

  13. Information Science and Engineering, Central South University, Changsha, Hunan, China

    Qin Liu

  14. Information Science and Engineering, Central South University, Changsha, Hunan, China

    Zakirul Alam Bhuiyan

  15. Ludwig Maximilian University of Munich, Munich, Germany

    Karl Fürlinger

  16. Informatik 10 - Rechnertechnik, Technische Universität München, Munich, Germany

    Josef Weidendorfer

  17. High Performance Computing Center (HLRS), Stuttgart, Germany

    José Gracia

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© 2016 Springer International Publishing AG

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Cremer, S., Bagein, M., Mahmoudi, S., Manneback, P. (2016). Efficiency of GPUs for Relational Database Engine Processing. In: Carretero, J., et al. Algorithms and Architectures for Parallel Processing. ICA3PP 2016. Lecture Notes in Computer Science(), vol 10049. Springer, Cham. https://doi.org/10.1007/978-3-319-49956-7_18

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  • DOI: https://doi.org/10.1007/978-3-319-49956-7_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49955-0

  • Online ISBN: 978-3-319-49956-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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