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dc.contributor.authorCano, Alberto
dc.contributor.authorZafra, Amelia
dc.contributor.authorVentura Soto, S.
dc.date.accessioned2017-01-19T13:30:17Z
dc.date.available2017-01-19T13:30:17Z
dc.date.issued2017-01-19
dc.identifier.urihttp://hdl.handle.net/10396/14347
dc.description.abstractIndividuals from Pittsburgh rule-based classifiers represent a complete solution to the classification problem and each individual is a variable-length set of rules. Therefore, these systems usually demand a high level of computational resources and run-time, which increases as the complexity and the size of the data sets. It is known that this computational cost is mainly due to the recurring evaluation process of the rules and the individuals as rule sets. In this paper we propose a parallel evaluation model of rules and rule sets on GPUs based on the NVIDIA CUDA programming model which significantly allows reducing the run-time and speeding up the algorithm. The results obtained from the experimental study support the great efficiency and high performance of the GPU model, which is scalable to multiple GPU devices. The GPU model achieves a rule interpreter performance of up to 64 billion operations per second and the evaluation of the individuals is speeded up of up to 3.461× when compared to the CPU model. This provides a significant advantage of the GPU model, especially addressing large and complex problems within reasonable time, where the CPU run-time is not acceptablees_ES
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoenges_ES
dc.rightshttps://creativecommons.org/licenses/by-nc-nd/4.0/es_ES
dc.subjectPittsburghes_ES
dc.subjectClassificationes_ES
dc.subjectRule setses_ES
dc.subjectParallel computinges_ES
dc.subjectGPUses_ES
dc.titleParallel evaluation of Pittsburgh rule-based classifiers on GPUses_ES
dc.typeinfo:eu-repo/semantics/preprintes_ES
dc.relation.projectIDJunta de Andalucía. P08-TIC-3720es_ES
dc.relation.projectIDGobierno de España. TIN- 2011-22408es_ES
dc.relation.projectIDGobierno de España. FPU-AP2010- 0042es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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