Statistical power profile correlation for realistic thermal estimation

Abstract

At system level, the on-chip temperature depends both on power density and the thermal coupling with the neighboring regions. The problem of finding the right set of input power profile(s) for accurate temperature estimation has not been studied. Considering only average or peak power density may lead either to underestimation or overestimation of the thermal crisis, respectively. To provide more realistic temperature estimation, we propose to incorporate multiple power profiles. Using the proposed statistical methods to determine the closeness between the power profiles, we apply a clustering algorithm to identify few input power profiles. We incorporate them in a thermal-aware floorplanner and empirical results show that using the single input power profile (average or peak) leads to 37% degradation in critical wire delay and 20% degradation in wire length, compared to using the multiple input power profiles.