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Symptom-based Fault Detection in Modern Computer Systems

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dc.contributor.authorBecker, Thomas
dc.contributor.authorRudolf, Nico
dc.contributor.authorYang, Dai
dc.contributor.authorKarl, Wolfgang
dc.date.accessioned2020-08-25T09:05:20Z
dc.date.available2020-08-25T09:05:20Z
dc.date.issued2020
dc.description.abstractMiniaturization and the increasing number of components, which get steadily more complex, lead to a rising failure rate in modern computer systems. Especially soft hardware errors are a major problem because they are usually temporary and therefore hard to detect. As classical fault-tolerance methods are very costly and reduce system efficiency, light-weight methods are needed to increase system reliability. A method that copes with this requirement is symptom-based fault detection. In this work, we evaluate the ability to detect different faults with symptom-based fault detection by using hardware performance counters. As the knowledge of a fault occurrence is usually not enough, we also evaluate the possibility to make conclusions about which fault occurred. For the evaluation, we used the fault-injection library FINJ and manually manipulated loops. The results show that symptom-based fault detection enables the system to detect faulty application behavior, however fine-grained conclusions about the causing fault are hardly possible.en
dc.identifier.pissn0177-0454
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/33864
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V., Fachgruppe PARS
dc.relation.ispartofPARS-Mitteilungen: Vol. 35, Nr. 1
dc.titleSymptom-based Fault Detection in Modern Computer Systemsen
dc.typeText/Journal Article
gi.citation.endPage50
gi.citation.publisherPlaceBerlin
gi.citation.startPage39

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