Investigating the Impact of Radiation-Induced Soft Errors on the Reliability of Approximate Computing Systems
Matana Luza, L., Söderström, D., Tsiligiannis, G., Puchner, H., Cazzaniga, C., Sanchez, E., Bosio, A., & Dilillo, L. (2020). Investigating the Impact of Radiation-Induced Soft Errors on the Reliability of Approximate Computing Systems. In L. Dilillo, M. Psarakis, & T. Siddiqua (Eds.), DFT 2020 : 33rd IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems. IEEE. Proceedings : IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems, 2020. https://doi.org/10.1109/DFT50435.2020.9250865
Julkaistu sarjassa
Proceedings : IEEE International Symposium on Defect and Fault Tolerance in VLSI SystemsTekijät
Päivämäärä
2020Tekijänoikeudet
© 2020 IEEE
Approximate Computing (AxC) is a well-known paradigm able to reduce the computational and power overheads of a multitude of applications, at the cost of a decreased accuracy. Convolutional Neural Networks (CNNs) have proven to be particularly suited for AxC because of their inherent resilience to errors. However, the implementation of AxC techniques may affect the intrinsic resilience of the application to errors induced by Single Events in a harsh environment. This work introduces an experimental study of the impact of neutron irradiation on approximate computing techniques applied on the data representation of a CNN.
Julkaisija
IEEEEmojulkaisun ISBN
978-1-7281-9458-5Konferenssi
IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology SystemsKuuluu julkaisuun
DFT 2020 : 33rd IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology SystemsISSN Hae Julkaisufoorumista
1550-5774Asiasanat
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/68030575
Metadata
Näytä kaikki kuvailutiedotKokoelmat
Rahoittaja(t)
Euroopan komissioRahoitusohjelmat(t)
The content of the publication reflects only the author’s view. The funder is not responsible for any use that may be made of the information it contains.
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Emulating the Effects of Radiation-Induced Soft-Errors for the Reliability Assessment of Neural Networks
Matanaluza, Lucas; Ruospo, Annachiara; Söderström, Daniel; Cazzaniga, Carlo; Kastriotou, Maria; Sanchez, Ernesto; Bosio, Alberto; Dilillo, Luigi (Institute of Electrical and Electronics Engineers (IEEE), 2022)Convolutional Neural Networks (CNNs) are currently one of the most widely used predictive models in machine learning. Recent studies have demonstrated that hardware faults induced by radiation fields, including cosmic rays, ... -
Effect of 20 MeV Electron Radiation on Long Term Reliability of SiC Power MOSFETs
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Proton Irradiation-Induced Reliability Degradation of SiC Power MOSFET
Niskanen, Kimmo; Kettunen, Heikki; Söderström, Daniel; Rossi, Mikko; Jaatinen, Jukka; Javanainen, Arto (Institute of Electrical and Electronics Engineers (IEEE), 2023)The effect of 53 MeV proton irradiation on the reliability of silicon carbide power MOSFETs was investigated. Post-irradiation gate voltage stress was applied and early failures in time-dependent dielectric breakdown (TDDB) ... -
Technology Impact on Neutron-Induced Effects in SDRAMs : A Comparative Study
Matana Luza, Lucas; Söderström, Daniel; Pio de Mattos, Andre Martins; Bezerra, Eduardo Augusto; Cazzaniga, Carlo; Kastriotou, Maria; Poivey, Christian; Dilillo, Luigi (IEEE, 2021)This study analyses the response of synchronous dynamic random access memories to neutron irradiation. Three different generations of the same device with different node sizes (63, 72, and 110 nm) were characterized under ... -
Impact of Terrestrial Neutrons on the Reliability of SiC VD-MOSFET Technologies
Martinella, Corinna; Alia, R. G.; Stark, R.; Coronetti, Andrea; Cazzaniga, C.; Kastriotou, M.; Kadi, Y.; Gaillard, R.; Grossner, U.; Javanainen, Arto (Institute of Electrical and Electronics Engineers (IEEE), 2021)Accelerated terrestrial neutron irradiations were performed on different commercial SiC power MOSFETs with planar, trench and double-trench architectures. The results were used to calculate the failure cross-sections and ...
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