A framework for enabling fault tolerance in reconfigurable architectures

Siozios, K; Soudris, D; Pnevmatikatos, D

dc.contributor.author	Siozios, K	en
dc.contributor.author	Soudris, D	en
dc.contributor.author	Pnevmatikatos, D	en
dc.date.accessioned	2014-03-01T02:46:36Z
dc.date.available	2014-03-01T02:46:36Z
dc.date.issued	2010	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32743
dc.subject	Fault Tolerant	en
dc.subject	reconfigurable architecture	en
dc.subject	Safety Critical System	en
dc.subject	Single Event Upset	en
dc.subject.other	Hardware elements	en
dc.subject.other	Performance degradation	en
dc.subject.other	Power overhead	en
dc.subject.other	Reconfigurable architecture	en
dc.subject.other	Safety critical systems	en
dc.subject.other	Single event upsets	en
dc.subject.other	Target architectures	en
dc.subject.other	Cavity resonators	en
dc.subject.other	Fault tolerance	en
dc.subject.other	Quality assurance	en
dc.title	A framework for enabling fault tolerance in reconfigurable architectures	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-642-12133-3_24	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-642-12133-3_24	en
heal.publicationDate	2010	en
heal.abstract	Fault tolerance is a pre-request not only for safety critical systems, but almost for the majority of applications. However, the additional hardware elements impose performance degradation. In this paper we propose a software-supported methodology for protecting reconfigurable architectures against Single Event Upsets (SEUs), even if the target device is not aware about this feature. This methodology initially predicts areas of the target architecture where faults are most possible to occur and then inserts selectively redundancy only there. Based on experimental results, we show that our proposed selectively fault-tolerance results to a better tradeoff between desired level of reliability and area, delay, power overhead. © 2010 Springer-Verlag.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-642-12133-3_24	en
dc.identifier.volume	5992 LNCS	en
dc.identifier.spage	257	en
dc.identifier.epage	268	en