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Dynamic Guardband Selection: Thermal-Aware Optimization for Unreliable Multi-Core Systems
- Source :
- IEEE Transactions on Computers. 68:53-66
- Publication Year :
- 2019
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2019.
-
Abstract
- Circuit aging has become the major reliability concern in current and upcoming technology nodes. For instance, Bias Temperature Instability (BTI) leads to an increase in the threshold voltage of a transistor. That, in turn, may prolong the critical path delay of the processor and eventually may lead to timing errors. In order to avoid aging-induced timing errors, designers employ guardbands either with respect to voltage or frequency. State-of-the-art techniques determine a guardband type at the circuit level at design time irrespective from the running workload at the system level. Our investigation revealed that generated temperatures by a running workload have the potential to play a key role in determining the appropriate guardband type with respect to system performance. Therefore, we propose a paradigm shift in designing guardbands: to select the guardband types on-the-fly with respect to the workload-induced temperatures aiming at optimizing for performance under temperature and reliability constraints. Moreover, different guardband types for different cores can be selected simultaneously when multiple applications with diverse properties suggest this to be useful. Our dynamic guardband selection allows for a higher performance compared to techniques that employ a fixed (at design time) guardband type throughout.
- Subjects :
- Multi-core processor
Computer science
Transistor
Hardware_PERFORMANCEANDRELIABILITY
02 engineering and technology
020202 computer hardware & architecture
Theoretical Computer Science
Reliability engineering
law.invention
Threshold voltage
Reliability (semiconductor)
Computational Theory and Mathematics
Hardware and Architecture
law
0202 electrical engineering, electronic engineering, information engineering
Key (cryptography)
Software
Selection (genetic algorithm)
Subjects
Details
- ISSN :
- 23263814 and 00189340
- Volume :
- 68
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Computers
- Accession number :
- edsair.doi...........8f870fbd88abf93ad8852a23080d4879
- Full Text :
- https://doi.org/10.1109/tc.2018.2848276