2013 IEEE 19th Real-Time and Embedded Technology and Applications Symposium (RTAS) (2013)
Philadelphia, PA, USA USA
Apr. 9, 2013 to Apr. 11, 2013
Buyoung Yun , EECS Dept., Univ. of Michigan, Ann Arbor, MI, USA
K. G. Shin , EECS Dept., Univ. of Michigan, Ann Arbor, MI, USA
Shige Wang , Gen. Motors Global R&D, Warren, MI, USA
Multi-core System-on-Chip (SoC) has become a popular execution platform for many embedded real-time systems that require high performance and low power-consumption. High temperature is known to accelerate the failure of deep submicron chips. To prevent such accelerated failures due to chip overheating, various thermal-aware scheduling (TAS) algorithms and dynamic thermal management (DTM) have been proposed and applied to mission/safety-critical applications. To control on-chip temperature more effectively, it is necessary to predict the thermal dynamics of a multi-core chip in real time and trigger appropriate power/temperature management before overheating the chip. However, due to dynamically-changing runtime environments, it is very difficult to estimate the chip temperature on-the-fly. In this paper, we propose models of efficiently estimating multi-core chip temperature while accounting for the system dynamics in real time. Based on these models, we design a proactive peak temperature manager (PTM) which periodically estimates future core temperature and triggers proper DTMs on the estimated-to-be-overheated cores for their cooling without violating applications timing constraints. Our in-depth evaluation based on the HotSpot thermal simulator has shown that the proposed method can predict the occurrence of peak temperature in a core with 90-98% accuracy, and using the estimated thermal model of a multi-core chip, PTM can effectively keep core temperature below a given threshold without violating any timing constraint.
Multicore processing, Runtime, Temperature measurement, Vectors, Temperature sensors, Predictive models, Timing
Buyoung Yun, K. G. Shin and Shige Wang, "Predicting thermal behavior for temperature management in time-critical multicore systems," 2013 IEEE 19th Real-Time and Embedded Technology and Applications Symposium (RTAS), Philadelphia, PA, USA USA, 2013, pp. 185-194.