Comparative analysis of exhaustive searching on a massive finger-vein database over multi-node/multi-core and multi-GPU platforms

When searching on unstructured data (video, images, etc.), response times are a critical factor. In this work we propose an implementation on two types of multi-GPU and multi-node/multi-core platforms, for massive searches. The presented method aims to reduce the time involved in the search process...

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Detalles Bibliográficos
Autores principales: Guidet, Sebastián, Hernández-García, Ruber, Frati, Fernando Emmanuel, Barrientos, Ricardo J.
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2022
Materias:
Ciencias Informáticas
High Performance Computing
identification of individuals
Local linear binary pattern
Finger veins
GPU
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/140636
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-140636
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
High Performance Computing
identification of individuals
Local linear binary pattern
Finger veins
GPU
spellingShingle Ciencias Informáticas
High Performance Computing
identification of individuals
Local linear binary pattern
Finger veins
GPU
Guidet, Sebastián
Hernández-García, Ruber
Frati, Fernando Emmanuel
Barrientos, Ricardo J.
Comparative analysis of exhaustive searching on a massive finger-vein database over multi-node/multi-core and multi-GPU platforms
topic_facet Ciencias Informáticas
High Performance Computing
identification of individuals
Local linear binary pattern
Finger veins
GPU
description When searching on unstructured data (video, images, etc.), response times are a critical factor. In this work we propose an implementation on two types of multi-GPU and multi-node/multi-core platforms, for massive searches. The presented method aims to reduce the time involved in the search process by solving simultaneous queries over the system and a database of millions of elements. The results show that the multi-GPU approach is 1.6 times superior to the multi-node/multi-core algorithm. Moreover, in both algorithms the speedup is directly proportional to the number of nodes reaching 156x for 4 GPUs, and 87x in the case of the hybrid multi-node/multi-core algorithm.
format Objeto de conferencia
Objeto de conferencia
author Guidet, Sebastián
Hernández-García, Ruber
Frati, Fernando Emmanuel
Barrientos, Ricardo J.
author_facet Guidet, Sebastián
Hernández-García, Ruber
Frati, Fernando Emmanuel
Barrientos, Ricardo J.
author_sort Guidet, Sebastián
title Comparative analysis of exhaustive searching on a massive finger-vein database over multi-node/multi-core and multi-GPU platforms
title_short Comparative analysis of exhaustive searching on a massive finger-vein database over multi-node/multi-core and multi-GPU platforms
title_full Comparative analysis of exhaustive searching on a massive finger-vein database over multi-node/multi-core and multi-GPU platforms
title_fullStr Comparative analysis of exhaustive searching on a massive finger-vein database over multi-node/multi-core and multi-GPU platforms
title_full_unstemmed Comparative analysis of exhaustive searching on a massive finger-vein database over multi-node/multi-core and multi-GPU platforms
title_sort comparative analysis of exhaustive searching on a massive finger-vein database over multi-node/multi-core and multi-gpu platforms
publishDate 2022
url http://sedici.unlp.edu.ar/handle/10915/140636
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