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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Contextual Spaces Re-Ranking: accelerating the Re-sort Ranked Lists step on heterogeneous systems

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Autor(es):
Pisani, Flavia [1] ; Pedronette, Daniel C. G. [2] ; Torres, Ricardo da S. [1] ; Borin, Edson [1]
Número total de Autores: 4
Afiliação do(s) autor(es):
[1] Univ Campinas UNICAMP, IC, Campinas, SP - Brazil
[2] Sao Paulo State Univ UNESP, Inst Geosci & Exact Sci IGCE, Rio Claro, SP - Brazil
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE; v. 29, n. 22, SI NOV 25 2017.
Citações Web of Science: 1
Resumo

Re-ranking algorithms have been proposed to improve the effectiveness of content-based image retrieval systems by exploiting contextual information encoded in distance measures and ranked lists. In this paper, we show how we improved the efficiency of one of these algorithms, called Contextual Spaces Re-Ranking (CSRR). One of our approaches consists in parallelizing the algorithm with OpenCL to use the central and graphics processing units of an accelerated processing unit. The other is to modify the algorithm to a version that, when compared with the original CSRR, not only reduces the total running time of our implementations by a median of 1.6x but also increases the accuracy score in most of our test cases. Combining both parallelization and algorithm modification results in a median speedup of 5.4x from the original serial CSRR to the parallelized modified version. Different implementations for CSRR's Re-sort Ranked Lists step were explored as well, providing insights into graphics processing unit sorting, the performance impact of image descriptors, and the trade-offs between effectiveness and efficiency. Copyright (c) 2016 John Wiley \& Sons, Ltd. (AU)

Processo FAPESP: 13/08645-0 - Reclassificação e agregação de listas para tarefas de recuperação de imagens
Beneficiário:Daniel Carlos Guimarães Pedronette
Linha de fomento: Auxílio à Pesquisa - Apoio a Jovens Pesquisadores