kNN Query Processing in Metric Spaces Using GPUs

  • Ricardo J. Barrientos
  • José I. Gómez
  • Christian Tenllado
  • Manuel Prieto Matias
  • Mauricio Marin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6852)

Abstract

Information retrieval from large databases is becoming crucial for many applications in different fields such as content searching in multimedia objects, text retrieval or computational biology. These databases are usually indexed off-line to enable an acceleration of on-line searches. Furthermore, the available parallelism has been exploited using clusters to improve query throughput. Recently some authors have proposed the use of Graphic Processing Units (GPUs) to accelerate brute-force searching algorithms for metric-space databases. In this work we improve existing GPU brute-force implementations and explore the viability of GPUs to accelerate indexing techniques. This exploration includes an interesting discussion about the performance of both brute-force and indexing-based algorithms that takes into account the intrinsic dimensionality of the element of the database.

Keywords

Graphic Processing Unit Memory Access Shared Memory Range Query Indexing Mechanism 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ricardo J. Barrientos
    • 1
  • José I. Gómez
    • 1
  • Christian Tenllado
    • 1
  • Manuel Prieto Matias
    • 1
  • Mauricio Marin
    • 2
  1. 1.Architecture Department of Computers and Automatic, ArTeCS GroupComplutense University of MadridMadridEspaña
  2. 2.Yahoo! Research Latin AmericaSantiagoChile

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