A GPU-based implementation for range queries on spaghettis data structure

Roberto Uribe-Paredes, Pedro Valero-Lara, Enrique Arias, José L. Sánchez, Diego Cazorla

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

Similarity search in a large collection of stored objects in a metric database has become a most interesting problem. The Spaghettis is an efficient metric data structure to index metric spaces. However, for real applications processing large volumes of generated data, query response times can be high enough. In these cases, it is necessary to apply mechanisms in order to significantly reduce the average query time. In this sense, the parallelization of metric structures is an interesting field of research. The recent appearance of GPUs for general purpose computing platforms offers powerful parallel processing capabilities. In this paper we propose a GPU-based implementation for Spaghettis metric structure. Firstly, we have adapted Spaghettis structure to GPU-based platform. Afterwards, we have compared both sequential and GPU-based implementation to analyse the performance, showing significant improvements in terms of time reduction, obtaining values of speed-up close to 10.

Original languageEnglish
Title of host publicationComputational Science and Its Applications, ICCSA 2011 - International Conference, Proceedings
Pages615-629
Number of pages15
EditionPART 1
DOIs
StatePublished - 2011
Externally publishedYes
Event2011 International Conference on Computational Science and Its Applications, ICCSA 2011 - Santander, Spain
Duration: Jun 20 2011Jun 23 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6782 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2011 International Conference on Computational Science and Its Applications, ICCSA 2011
Country/TerritorySpain
CitySantander
Period06/20/1106/23/11

Funding

This work has been partially funded by research programs PR-F1-02IC-08, University of Magallanes, Chile and 29/C035-1, Academic Unit of Río Turbio, National University of Patagonia Austral, Argentina, and the Spanish project SAT-SIM (ref: CGL2010-20787-C02-02).

FundersFunder number
National University of Patagonia AustralCGL2010-20787-C02-02
Universidad de Magallanes29/C035-1

    Keywords

    • CUDA
    • Databases
    • GPU
    • algorithms
    • data structures
    • metric spaces
    • parallel processing
    • similarity search

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