Abstract
Nowadays, a rapid introduction of very complex nanometer Many-Processor Systems-on-Chip in safety-critical applications is taking place. Unfortunately, it pairs with an unacceptable decrease in dependability of these complex nanosystems if no additional countermeasures are taken. To address this challenge, a promising approach is presented in this paper that uses a set of IJTAG compatible embedded instruments (EIs), in and around a processor cores to monitor their present health status. Data from these EIs is collected and fused for lifetime prognostics and hence dependability. For the EIs data fusion, use is made of principal component analysis (PCA) technique. For lifetime prediction based on different EIs, power-law degradation model was used.
Original language | English |
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Title of host publication | IEEE International Symposium on Circuits and Systems, ISCAS 2020 |
Place of Publication | Piscataway, NJ |
Publisher | IEEE |
Pages | 1-5 |
Number of pages | 5 |
ISBN (Electronic) | 978-1-7281-3320-1 |
ISBN (Print) | 978-1-7281-3321-8 |
DOIs | |
Publication status | Published - 28 Sept 2020 |
Event | 52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Virtual Conference, Virtual, Online, Spain Duration: 10 Oct 2020 → 21 Oct 2020 Conference number: 52 https://www.iscas2020.org/ |
Publication series
Name | IEEE International Symposium on Circuits and Systems (ISCAS) |
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Publisher | IEEE |
Volume | 2020 |
ISSN (Print) | 0271-4302 |
ISSN (Electronic) | 2158-1525 |
Conference
Conference | 52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020 |
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Abbreviated title | ISCAS 2020 |
Country/Territory | Spain |
City | Virtual, Online |
Period | 10/10/20 → 21/10/20 |
Internet address |
Keywords
- Dependability
- Embedded instruments
- Data fusion
- Machine learning
- n/a OA procedure