An improved thermal model for static optimization of application mapping and scheduling in multiprocessor system-on-chip

With the increasing power density and numberof cores integrated into a single chip, thermal managementis widely recognized as one of the essential issues in Multi-Processor Systems-on-Chip (MPSoCs). An uncontrolled temperaturecould significantly decrease system performance, leadto high cooling and packaging costs, and even cause seriousdamage. These issues have made temperature one of themajor factors that must be addressed in MPSoC designs. Static scheduling of applications should take the thermaleffects of task executions into consideration to keep the chiptemperature under a safety threshold. However, inaccuratetemperature estimation would cause processor overheating orsystem performance degradation. In this paper, we proposean improved thermal modeling technique that can be used topredict the chip temperature more accurately and efficiently atdesign time. We further develop a simulated annealing (SA)-based algorithm to address the static application mapping andscheduling problem based on the improved thermal model. Thethermal condition is greatly improved and the total energyconsumption is minimized. Experimental results show thatthe improved thermal modeling technique could provide anaverage of over 99% accuracy of temperature prediction whencomparing with the results offered by Hotspot simulations. Based on it, the SA-based algorithm could reduce the chancesthat the temperature threshold to be violated at runtime by24.3%.