Estimation of energy performance in computing platforms

Abstract

System-level estimation of speed and energy performance is a key step in design space exploration of low-energy and high-performance VLSI systems. While low-level simulation-based analysis can be too time-consuming to obtain performance elements, system-level models that can quickly and accurately estimate these elements are very valuable. In this work, models for energy performance estimation of computing platforms are proposed. The proposed energy performance models are inspired by Amdahl's law. The models consider platform models based on the support of power gating. Analytical results show that the upper-bound of energy performance, according to the application profile is the ¿resolute¿ (that cannot be enhanced) segment of the (embedded) software application. This is a similar concern to the one seen for ¿net acceleration¿ (the speed performance) being bounded by the ¿sequential¿ segment, according to Amdahl's law. Experimental results demonstrate that large improvements in energy performance may be obtained using power gating for both data and control dominated classes of applications (2 and 12 folds respectively). The results also demonstrate an average error of 22% between the proposed system-level models and true experimental results for three classes of applications.