Joint Work and Voltage/Frequency Scaling for Quality-Optimized Dynamic Thermal Management

Abstract

Dynamic thermal management (DTM) is commonly used to ensure reliable and safe operation in modern computing systems. DTM techniques are based on slowing down or shutting down parts of a system; hence, they effectively reduce system performance and thereby adversely impact applications. In this paper, we focus on real-time applications in which degradation in performance translates to a loss in application quality, and address the problem of quality-optimized DTM, wherein the objective of DTM is to satisfy specified temperature constraints while optimizing application quality metrics. We first introduce a new DTM method called dynamic work scaling (DWS), which is based on modulating an application’s computational requirements. Next, we observe that application quality and platform temperature are effectively determined by two key parameters, viz., the application’s computational requirement and the platform’s computing capacity, and formulate the relationship between them. Finally, we propose a quality-optimized DTM based on joint dynamic work and voltage/frequency scaling (DWVFS). We have implemented the proposed DTM technique and evaluated it for two applications: 1) H.264 video encoding and 2) turbo decoding. Our results demonstrate that DWVFS can provide superior results in terms of application quality compared with both DVFS and DWS-based DTM at identical temperature constraints.