Abstraction and microarchitecture scaling in early-stage power modeling

Abstract

Early-stage, microarchitecture-level power modeling methodologies have been used in industry and academic research for a decade (or more). Such methods use cycle-accurate performance simulators and deduce active power based on utilization markers. A key question faced in this context is: what key utilization metrics to monitor, and how many are needed for accuracy? Is there a systematic way to select the “best” markers? We also pose a key follow-on question: is it possible to perform accurate scaling of an abstracted model to enable exploration of new microarchitecture features? In this paper, we address these particular questions and examine the results for a range of abstraction levels. We highlight innovative insights for intelligent abstraction and microarchitecture scaling, and point out the pitfalls of abstractions that are not based on a systematic methodology or sound theory.