Resilience and Real-Time Constrained Energy Optimization in Embedded Processor Systems

Low power embedded processing is known to rely on dynamic voltage-frequency scaling (DVFS) in order to optimize energy usage (and therefore battery life). However, low voltage operation exacerbates the incidence of soft errors. Similarly, higher voltage operation (to meet real-time deadlines) is constrained by power dissipation (and associated thermal) maxima as dictated by hard failure rate limits. In this paper, we introduce a novel modeling framework called PEARL to examine a class of embedded system applications relevant to mobile, airborne vehicles. Using PEARL, we investigate the problem of assigning optimal voltage-frequency settings to individual segments within example workflows. The workflows are synthesized from the selected applications; and, the goal of this study is to understand the limits of achievable energy efficiency (performance/Watt) under varying levels of system resilience targets. The analysis results show that: (a) the resilience constraints are critical in determining the limits of achievable efficiency; and (b) higher variability in power dissipation across workflow segments enables a larger boost in efficiency, despite stringent resilience constraints. Keywords-low power, embedded systems, soft error resilience, real-time constraints