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Improving Performances of an Embedded Relational Database Management System with a Hybrid CPU/GPU Processing Engine

  • Samuel CremerEmail author
  • Michel Bagein
  • Saïd Mahmoudi
  • Pierre Manneback
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 737)

Abstract

End-user systems are increasingly impacted by the exponential growth of data volumes and their processing. Moreover, post-processing operations, essentially dedicated to ergonomic features, require more and more resources. Improving overall performances of embedded relational database management systems (RDBMS) can contribute to deliver better responsiveness of end-user systems while increasing the energy efficiency. In this paper, it is proposed to upgrade SQLite, the most-spreaded embedded RDBMS, with a hybrid CPU/GPU processing engine combined with appropriate data management. With the proposed solution, named CuDB, massively parallel processing is combined with strategic data placement, closer to computing units. Experimental results revealed, in all cases, better performances and power efficiency compared to SQLite with an in-memory database.

Keywords

In-memory database systems Embedded databases Relational database management systems GPU 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Samuel Cremer
    • 1
    • 2
    Email author
  • Michel Bagein
    • 2
  • Saïd Mahmoudi
    • 2
  • Pierre Manneback
    • 2
  1. 1.Computer Engineering DepartmentHaute Ecole en HainautMonsBelgium
  2. 2.Computer Science DepartmentUniversity of MonsMonsBelgium

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