Speeding Up Evolutionary Learning Algorithms using GPUs

dc.contributor.author	Cano, Alberto
dc.contributor.author	Zafra, Amelia
dc.contributor.author	Ventura Soto, S.
dc.date.accessioned	2013-08-30T10:26:08Z
dc.date.available	2013-08-30T10:26:08Z
dc.date.issued	2010
dc.identifier.uri	http://hdl.handle.net/10396/10874
dc.description.abstract	This paper propose a multithreaded Genetic Programming classi cation evaluation model using NVIDIA CUDA GPUs to reduce the computational time due to the poor perfor- mance in large problems. Two di erent clas- si cation algorithms are benchmarked using UCI Machine Learning data sets. Experi- mental results compare the performance us- ing single and multithreaded Java, C and GPU code and show the e ciency far better obtained by our proposal.	es_ES
dc.format.mimetype	application/pdf	es_ES
dc.language.iso	eng	es_ES
dc.publisher	ESTYLF	es_ES
dc.rights	https://creativecommons.org/licenses/by-nc-nd/4.0/	es_ES
dc.source	En: XV Congreso Español Sobre Tecnologías y Lógica Fuzzy, ESTYLF 2010, Huelva, 3 a 5 de febrero de 2010	es_ES
dc.subject	GPUs	es_ES
dc.subject	CUDA	es_ES
dc.subject	Genetic programming	es_ES
dc.title	Speeding Up Evolutionary Learning Algorithms using GPUs	es_ES
dc.type	info:eu-repo/semantics/conferenceObject	es_ES
dc.rights.accessRights	info:eu-repo/semantics/openAccess	es_ES