Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/50507
Campo DC Valoridioma
dc.contributor.authorSantana, Oliverio J.en_US
dc.contributor.authorRamirez, Alexen_US
dc.contributor.authorValero, Mateoen_US
dc.date.accessioned2018-11-24T16:34:29Z-
dc.date.available2018-11-24T16:34:29Z-
dc.date.issued2003en_US
dc.identifier.isbn0-7695-2019-7en_US
dc.identifier.issn1537-3223en_US
dc.identifier.urihttp://hdl.handle.net/10553/50507-
dc.description.abstractThe access latency of branch predictors is a well known problem of fetch engine design. Prediction overriding techniques are commonly accepted to overcome this problem. However, prediction overriding requires a complex recovery mechanism to discard the wrong speculative work based on overridden predictions. In this paper, we show that stream and trace predictors, which use long basic prediction units, can tolerate access latency without needing overriding, thus reducing fetch engine complexity. We show that both the stream fetch engine and the trace cache architecture not using overriding outperform other efficient fetch engines, such as an EV8-like fetch architecture or the FTB fetch engine, even when they do use overriding.en_US
dc.languageengen_US
dc.sourceProceedings of the Innovative Architecture for Future Generation High-Performance Processors and Systems [ISSN 1537-3223], v. 2003-January (1262780), p. 30-39en_US
dc.subject330406 Arquitectura de ordenadoresen_US
dc.titleLatency tolerant branch predictorsen_US
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.typeConferenceObjectes
dc.identifier.doi10.1109/IWIA.2003.1262780en_US
dc.identifier.scopus84888364700-
dc.identifier.isi000189420800004-
dc.contributor.authorscopusid7003605046-
dc.contributor.authorscopusid55837529000-
dc.contributor.authorscopusid24475914200-
dc.description.lastpage39-
dc.identifier.issue1262780-
dc.description.firstpage30-
dc.relation.volume2003-January-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.identifier.ulpgces
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptGIR SIANI: Inteligencia Artificial, Robótica y Oceanografía Computacional-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0001-7511-5783-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNameSantana Jaria, Oliverio Jesús-
Colección:Actas de congresos
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