Adaptive Power monitoring for self-aware embedded systems - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Conference Papers Year : 2015

Adaptive Power monitoring for self-aware embedded systems

Mohamad Najem
  • Function : Author
Pascal Benoit
Gilles Sassatelli
Lionel Torres

Abstract

Dynamic Thermal and Power Management methods require efficient monitoring techniques. Based on a set of data collected by sensors, embedded models estimate online the power consumption: this task is a real challenge, since models must be both accurate and low cost, but they also have to be robust to variations. In this paper, we investigate a self-aware approach using the performance events and the external temperature. We present a solution (PESel) for the selection of the relevant information. This method is two times faster than existing solutions and provides better results compared to related works. The power models achieve a 96% accuracy with a temporal resolution of 100 ms, and negligible performance/energy overheads (less than 1%). Moreover, we show that our estimations are not sensitive to external temperature variations.
Fichier principal
Vignette du fichier
NORCAS_Adaptive_Power_Monitoring.pdf (330.85 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

lirmm-01257519 , version 1 (17-01-2016)

Identifiers

Cite

Mohamad El Ahmad, Mohamad Najem, Pascal Benoit, Gilles Sassatelli, Lionel Torres. Adaptive Power monitoring for self-aware embedded systems. NORCAS 2015 - 1st Nordic Circuits and Systems Conference, Oct 2015, Oslo, Norway. ⟨10.1109/NORCHIP.2015.7364364⟩. ⟨lirmm-01257519⟩
204 View
286 Download

Altmetric

Share

Gmail Facebook X LinkedIn More