Chapter

Transactions on Large-Scale Data- and Knowledge-Centered Systems XV

Volume 8920 of the series Lecture Notes in Computer Science pp 1-35

Date:

GPU-Accelerated Database Systems: Survey and Open Challenges

  • Sebastian BreßAffiliated withUniversity of Magdeburg Email author 
  • , Max HeimelAffiliated withTechnische Universität Berlin
  • , Norbert SiegmundAffiliated withUniversity of Passau
  • , Ladjel BellatrecheAffiliated withLIAS/ISAE-ENSMA
  • , Gunter SaakeAffiliated withUniversity of Magdeburg

Abstract

The vast amount of processing power and memory bandwidth provided by modern graphics cards make them an interesting platform for data-intensive applications. Unsurprisingly, the database research community identified GPUs as effective co-processors for data processing several years ago. In the past years, there were many approaches to make use of GPUs at different levels of a database system. In this paper, we explore the design space of GPU-accelerated database management systems. Based on this survey, we present key properties, important trade-offs and typical challenges of GPU-aware database architectures, and identify major open challenges. Additionally, we survey existing GPU-accelerated DBMSs and classify their architectural properties. Then, we summarize typical optimizations implemented in GPU-accelerated DBMSs. Finally, we propose a reference architecture, indicating how GPU acceleration can be integrated in existing DBMSs.

Keywords

GPU-accelerated database Survey Co-processing Modern database architecture