kNN Query Processing in Metric Spaces Using GPUs

Ricardo J. Barrientos, Jose I. Gomez, Christian Tenllado, Manuel Prieto Matias, Mauricio Marin
Architecture Department of Computers and Automatic, ArTeCS Group, Complutense University of Madrid, Madrid, Espana
EURO-PAR 2011 Parallel Processing, Lecture Notes in Computer Science, Volume 6852/2011, 380-392, 2011


   title={kNN Query Processing in Metric Spaces Using GPUs},

   author={Barrientos, R. and G{‘o}mez, J. and Tenllado, C. and Matias, M. and Marin, M.},

   journal={Euro-Par 2011 Parallel Processing},





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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.
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