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dc.contributor.author
Tommasel, Antonela
dc.contributor.author
Godoy, Daniela Lis
dc.contributor.author
Zunino Suarez, Alejandro Octavio
dc.contributor.author
Mateos Diaz, Cristian Maximiliano
dc.date.available
2018-09-06T18:50:46Z
dc.date.issued
2017-05
dc.identifier.citation
Tommasel, Antonela; Godoy, Daniela Lis; Zunino Suarez, Alejandro Octavio; Mateos Diaz, Cristian Maximiliano; A distributed approach for accelerating sparse matrix arithmetic operations for high-dimensional feature selection; Springer London Ltd; Knowledge And Information Systems; 51; 2; 5-2017; 459-497
dc.identifier.issn
0219-1377
dc.identifier.uri
http://hdl.handle.net/11336/58575
dc.description.abstract
Matrix computations are both fundamental and ubiquitous in computational science, and as a result, they are frequently used in numerous disciplines of scientific computing and engineering. Due to the high computational complexity of matrix operations, which makes them critical to the performance of a large number of applications, their efficient execution in distributed environments becomes a crucial issue. This work proposes a novel approach for distributing sparse matrix arithmetic operations on computer clusters aiming at speeding-up the processing of high-dimensional matrices. The approach focuses on how to split such operations into independent parallel tasks by considering the intrinsic characteristics that distinguish each type of operation and the particular matrices involved. The approach was applied to the most commonly used arithmetic operations between matrices. The performance of the presented approach was evaluated considering a high-dimensional text feature selection approach and two real-world datasets. Experimental evaluation showed that the proposed approach helped to significantly reduce the computing times of big-scale matrix operations, when compared to serial and multi-thread implementations as well as several linear algebra software libraries.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Springer London Ltd
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.subject
Distributed Computing
dc.subject
Feature Selection
dc.subject
Matrix Arithmetic Operation
dc.subject
Sparse Matrix
dc.subject.classification
Ciencias de la Computación
dc.subject.classification
Ciencias de la Computación e Información
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
A distributed approach for accelerating sparse matrix arithmetic operations for high-dimensional feature selection
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2018-09-05T16:11:49Z
dc.journal.volume
51
dc.journal.number
2
dc.journal.pagination
459-497
dc.journal.pais
Reino Unido
dc.journal.ciudad
London
dc.description.fil
Fil: Tommasel, Antonela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
dc.description.fil
Fil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
dc.description.fil
Fil: Zunino Suarez, Alejandro Octavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
dc.description.fil
Fil: Mateos Diaz, Cristian Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
dc.journal.title
Knowledge And Information Systems
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1007/s10115-016-0981-5
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs10115-016-0981-5


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