Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/351034
Type: Artigo
Title: Approximate similarity search for online multimedia services on distributed CPU-GPU platforms
Author: Mariano, N.
Torres, R.
Teodoro, G.
Valle, E.
Meira, W.
Saltz, J. H.
Abstract: Similarity search in high-dimensional spaces is a pivotal operation for several database applications, including online content-based multimedia services. With the increasing popularity of multimedia applications, these services are facing new challenges regarding (1) the very large and growing volumes of data to be indexed/searched and (2) the necessity of reducing the response times as observed by end-users. In addition, the nature of the interactions between users and online services creates fluctuating query request rates throughout execution, which requires a similarity search engine to adapt to better use the computation platform and minimize response times. In this work, we address these challenges with Hypercurves, a flexible framework for answering approximate k-nearest neighbor (kNN) queries for very large multimedia databases. Hypercurves executes in hybrid CPU-GPU environments and is able to attain massive query-processing rates through the cooperative use of these devices. Hypercurves also changes its CPU-GPU task partitioning dynamically according to the observed load, aiming for optimal response times. In our empirical evaluation, dynamic task partitioning reduced query response times by approximately 50 % compared to the best static task partition. Due to a probabilistic proof of equivalence to the sequential kNN algorithm, the CPU-GPU execution of Hypercurves in distributed (multi-node) environments can be aggressively optimized, attaining superlinear scalability while still guaranteeing, with high probability, results at least as good as those from the sequential algorithm
Subject: Indexação
Banco de dados
Country: Estados Unidos
Editor: Association for Computing Machinery
Rights: Fechado
Identifier DOI: 10.1007/s00778-013-0329-7
Address: https://link.springer.com/article/10.1007/s00778-013-0329-7
Date Issue: 2014
Appears in Collections:IC - Artigos e Outros Documentos
FEEC - Artigos e Outros Documentos

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.