dc.creator | Spyrou, Theofilos | es |
dc.creator | El-Sayed, Sarah A. | es |
dc.creator | Afacan, Engin | es |
dc.creator | Camuñas Mesa, Luis Alejandro | es |
dc.creator | Linares Barranco, Bernabé | es |
dc.creator | Stratigopoulos, Haralampos G. | es |
dc.date.accessioned | 2023-01-19T10:36:08Z | |
dc.date.available | 2023-01-19T10:36:08Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Spyrou, T., El-Sayed, S.A., Afacan, E., Camuñas Mesa, L.A., Linares Barranco, B. y Stratigopoulos, H.G. (2021). Neuron fault tolerance in spiking neural networks. En 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE) (743-748), Grenoble, France: Institute of Electrical and Electronics Engineers. IEEE. | |
dc.identifier.issn | 1530-1591 | es |
dc.identifier.uri | https://hdl.handle.net/11441/141573 | |
dc.description.abstract | The error-resiliency of Artificial Intelligence (AI)
hardware accelerators is a major concern, especially when they
are deployed in mission-critical and safety-critical applications.
In this paper, we propose a neuron fault tolerance strategy for
Spiking Neural Networks (SNNs). It is optimized for low area and
power overhead by leveraging observations made from a largescale fault injection experiment that pinpoints the critical fault
types and locations. We describe the fault modeling approach,
the fault injection framework, the results of the fault injection
experiment, the fault-tolerance strategy, and the fault-tolerant
SNN architecture. The idea is demonstrated on two SNNs that
we designed for two SNN-oriented datasets, namely the N-MNIST
and IBM’s DVS128 gesture datasets. | es |
dc.description.sponsorship | Junta de Andalucía-US-1260118 | es |
dc.description.sponsorship | Universidad de Sevilla-VI PPIT | es |
dc.format | application/pdf | es |
dc.format.extent | 6 p. | es |
dc.language.iso | eng | es |
dc.publisher | Institute of Electrical and Electronics Engineers. IEEE | es |
dc.relation.ispartof | 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE) (2021), pp. 743-748. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | Neuron fault tolerance in spiking neural networks | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/acceptedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Electrónica y Electromagnetismo | es |
dc.relation.projectID | US-1260118 | es |
dc.relation.projectID | VI PPIT USE | es |
dc.relation.publisherversion | https://dx.doi.org/10.23919/DATE51398.2021.9474081 | es |
dc.identifier.doi | 10.23919/DATE51398.2021.9474081 | es |
dc.journaltitle | Design, Automation & Test in Europe Conference & Exhibition (DATE) | es |
dc.publication.issue | 9474081 | es |
dc.publication.initialPage | 743 | es |
dc.publication.endPage | 748 | es |
dc.eventtitle | 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE) | |
dc.eventinstitution | Grenoble, France | |
dc.contributor.funder | Junta de Andalucía | es |
dc.contributor.funder | Universidad de Sevilla | es |