Exploiting dynamic phase distance mapping for phase-based tuning of embedded systems

摘要

Phase-based tuning increases optimization potential by configuring system parameters for application execution phases. Previous work proposed phase distance mapping (PDM), which relied on extensive a priori analysis of executing applications to dynamically estimate the best configuration using the correlation between phases. We propose DynaPDM, a new dynamic phase distance mapping methodology that eliminates a priori designer effort, dynamically analyzes phases, and determines the best configurations, yielding average energy delay product savings of 28%—an 8% improvement on PDM—and configurations within 1% of the optimal.