Dynamic On-Chip Thermal Sensor Calibration Using Performance Counters
| Autor: | Russell Tessier, Shiting Justin Lu, Wayne Burleson |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Process variation
Computer science Approximation error Thermal Hardware_INTEGRATEDCIRCUITS Calibration Electronic engineering Hardware_PERFORMANCEANDRELIABILITY Thermal management of electronic devices and systems Electrical and Electronic Engineering Sensor fusion Computer Graphics and Computer-Aided Design Software |
| Zdroj: | IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 33:853-866 |
| ISSN: | 1937-4151 0278-0070 |
| DOI: | 10.1109/tcad.2014.2302384 |
| Popis: | Numerous sensors are currently deployed in modern processors to collect thermal information for fine-grained dynamic thermal management (DTM). Due to process variation and silicon aging, on-chip thermal sensors require periodic calibration before use in DTM. However, the calibration cost for thermal sensors can be prohibitively high as the number of on-chip sensors increases. In this paper, a model which is suitable for online calculation is employed to estimate the temperatures of multiple sensor locations on the silicon die. The estimated sensor and actual sensor thermal profile show a very high similarity with correlation coefficient ${\sim}{\rm 0.9}$ for most tested benchmarks. Our calibration approach combines potentially inaccurate temperature values obtained from two sources: temperature readings from thermal sensors and temperature estimations using system performance counters. A data fusion strategy based on Bayesian inference, which combines information from these two sources, is demonstrated along with a temperature estimation approach using performance counters. The average absolute error of the corrected sensor temperature readings is ${ and the standard deviation of error is less than ${ for tested benchmarks. |
| Databáze: | OpenAIRE |
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