Similarity Search of Sparse Histograms on GPU Architecture

Conférence Chapitre d'actes Similarity Search of Sparse Histograms on GPU Architecture eng 2016 author Osipyan Hasmik 810433 author Lokoč Jakub author Marchand-Maillet Stéphane 0000-0002-4875-6101 518563 325-338 10.1007/978-3-319-46759-7_25 978-3-319-46758-0 http://link.springer.com/10.1007/978-3-319-46759-7_25 Searching for similar objects within large-scale database is a hard problem due to the exponential increase of multimedia data. The time required to find the nearest objects to the specific query in a high-dimensional space has become a serious constraint of the searching algorithms. One of the possible solution for this problem is utilization of massively parallel platforms such as GPU architectures. This solution becomes very sensitive for the applications working with sparse dataset. The performance of the algorithm can be totally changed depending on the different sparsity settings of the input data. In this paper, we study four different approaches on the GPU architecture for finding the similar histograms to the given queries. The performance and efficiency of observed methods were studied on sparse dataset of half a million histograms. We summarize our empirical results and point out the optimal GPU strategy for sparse histograms with different sparsity settings. GPU Similarity search High-dimensional space Sparse dataset Dewey 025.063 Cham Springer International Publishing 13 Centre universitaire d'informatique 0D3 32 Département d'informatique 18 false 895 Computer Vision and Multimedia Laboratory 675 Viper group Similarity Search and Applications, 9th International Conference, SISAP 2016 24-26 October 2016 Tokyo (Japan) f3fd834a-dac3-4497-8036-a2f2ddb0d63e Proceedings chapter (Published version) Restricted 2016Osipyan_similarity_search.pdf 708726 application/pdf restrictedAccess Centres et instituts / Centre universitaire d'informatique Faculté des sciences / Département d'informatique

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Similarity Search of Sparse Histograms on GPU Architecture	Similarity Search and Applications, 9th International Conference, SISAP 2016			2016	350	0

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Osipyan, Hasmik