PowerProbe: Run-time Power Modeling Through Automatic RTL Instrumentation

Davide Zonia, Luca Cremonab and William Fornaciaric
Politecnico di Milano ‐ Dipartimento di Elettronica e Informazione Milano, Italy
adavide.zoni@polimi.it
bluca2.cremona@mail.polimi.it
cwilliam.fornaciari@polimi.it

ABSTRACT


Online power monitoring represents a de‐facto solution to enable energy‐ and power‐aware run‐time optimizations for current and future computing architectures. Traditionally, the performance counters of the target architecture are used to feed a software-based, power model that is continuously updated to deliver the required run-time power estimates. The solution introduces a non-negligible performance and energy overhead. Moreover, it is limited to the availability of such performance counters that, however, are not primarily intended for online power monitoring. This paper introduces PowerProbe, a run‐time power monitoring methodology that automatically extracts and implements a power model from the RTL description of the target architecture. The solution does not leverage any performance counter to ensure wide applicability. Moreover, the use of ad‐hoc hardware that continuously updates the power estimate minimizes both the performance and the power overheads. We employ a fully compliant OpenRisc 1000 implementation to validate PowerProbe. The results highlight an average prediction error within 9% (standard deviation less than 2%), with a power and area overheads limited to 6.89% and 4.71%, respectively.

Keywords: Low Power, Run‐Time, Power Modeling, RTL.


Full Text (PDF)