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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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info:eu-repo/semantics/openAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Atribución-NoComercial-SinDerivadas 2.5 Argentina (CC BY-NC-ND 2.5 AR)