Real-Time IC Aging Prediction via On-Chip Sensors
| dc.contributor.author | Huang, Ke | |
| dc.contributor.author | Anik, Md Toufiq Hasan | |
| dc.contributor.author | Zhang, Xinqiao | |
| dc.contributor.author | Karimi, Naghmeh | |
| dc.date.accessioned | 2021-07-28T18:31:29Z | |
| dc.date.available | 2021-07-28T18:31:29Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Real-time aging prediction for nanoscale integrated circuits (ICs) is a crucial step for developing prevention and mitigation actions to avoid unexpected circuit failures in the field of operation. Current practices for predicting aging-related performance degradation in ICs consist of recording the operating conditions (e.g. workload, temperature, etc.) throughout ICs’ usage time and building a learning model that maps historical operating conditions to actual performance degradation. While some operating conditions such as IC workload can be readily recorded using existing on-chip structures (e.g. registers), other operating conditions such as historical temperature values may not be available for real-time aging degradation prediction. In this paper, we develop a novel real-time IC aging prediction scheme using a set of on-chip sensors that can accurately record historical operating condition parameter values, which will in turn be used for aging-related performance degradation prediction. Experimental results show that by using a machine learning based prediction model and the notion of equivalent aging time, we can achieve accurate aging degradation prediction with the proposed on-chip sensor structure. | en_US |
| dc.description.sponsorship | This work was partly funded by the Strategic Awards for Research Transitions (START) program at UMBC. | en_US |
| dc.description.uri | https://www.csee.umbc.edu/~nkarimi/papers/ISVLSI21_b.pdf | en_US |
| dc.format.extent | 6 pages | en_US |
| dc.genre | journal articles preprints | en_US |
| dc.identifier | doi:10.13016/m2qems-9naz | |
| dc.identifier.uri | http://hdl.handle.net/11603/22203 | |
| dc.language.iso | en_US | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
| dc.title | Real-Time IC Aging Prediction via On-Chip Sensors | en_US |
| dc.type | Text | en_US |