Modern low power designs use multiple knobs for concurrent dynamic and leakage power optimization; supply voltage and threshold voltage are the most adopted. An efficient control of these knobs needs management policies aware of the power breakdown. This implies the availability of smart on-chip strategies for dynamic and leakage power estimation at runtime. In this paper, we address this issue proposing the implementation of embedded dynamic/static power meters that use an optimized regression model fed with data collected from in-situ activity monitors. The number of sensors, their bitwidth and optimal placement are obtained through an automated design flow. The methodology works for general logic and applies not just to processor cores, but also to application-specific designs. We apply our solution to a representative class of benchmarks, showing that it can achieve an average estimation error smaller than 3%, with limited area and power overheads.
All-digital embedded meters for on-line power estimation / Jahier Pagliari, Daniele; Peluso, Valentino; Chen, Yukai; Calimera, Andrea; Macii, Enrico; Poncino, Massimo. - ELETTRONICO. - (2018), pp. 737-742. (Intervento presentato al convegno 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE) tenutosi a Dresden, Germany nel 19-23 March 2018) [10.23919/DATE.2018.8342105].
All-digital embedded meters for on-line power estimation
Jahier Pagliari, Daniele;Peluso, Valentino;Chen, Yukai;Calimera, Andrea;Macii, Enrico;Poncino, Massimo
2018
Abstract
Modern low power designs use multiple knobs for concurrent dynamic and leakage power optimization; supply voltage and threshold voltage are the most adopted. An efficient control of these knobs needs management policies aware of the power breakdown. This implies the availability of smart on-chip strategies for dynamic and leakage power estimation at runtime. In this paper, we address this issue proposing the implementation of embedded dynamic/static power meters that use an optimized regression model fed with data collected from in-situ activity monitors. The number of sensors, their bitwidth and optimal placement are obtained through an automated design flow. The methodology works for general logic and applies not just to processor cores, but also to application-specific designs. We apply our solution to a representative class of benchmarks, showing that it can achieve an average estimation error smaller than 3%, with limited area and power overheads.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2709739