Processors in cyber-physical systems are increasingly being used in applications where they must operate in harsh ambient conditions and a computational workload which can lead to high chip temperatures. Examples include cars, robots, aircraft and spacecraft. High operating temperatures accelerate the aging of the chips, thus increasing transient and permanent failure rates. Current ways to deal with this mostly turn off the processor core or drastically slow it down when some part of it is seen to exceed a given temperature threshold. However, this pass/fail approach ignores the fact that (a) processors experience accelerated aging due to high temperatures, even if these are below the threshold, and (b) while deadlines are a constraint for real-time tasks to keep the controlled plant in the allowed state space, the actual controller response times that will increase if the voltage or frequency is lowered (to cool down the chip) are what determine the controlled plant performance. Existing approaches also fail to exploit the tradeoff between controller reliability (affected by its temperature history) and the performance of the plant. This project addresses these issues. Load-shaping algorithms are being devised to manage thermal stresses while ensuring appropriate levels of control quality. Such actions include task migration, changing execution speed, selecting an alternative algorithm or software implementation of control functions, and terminating prematurely optional portions of iterative tasks. Validation platforms for this project include automobiles and unmanned aerial vehicles. These platforms have been chosen based on both their importance to society and the significant technical challenges they pose. With CPS becoming ever more important in our lives and businesses, this project which will make CPS controllers more reliable and/or economical has broad potential social and economic impacts. Collaboration with General Motors promotes transition of the new technology to industry. The project includes activities to introduce students to thermal control in computing, in courses spanning high-school, undergraduate and graduate curricula.

Processors in cyber-physical systems are increasingly being used in applications where they must operate in harsh ambient conditions and a computational workload which can lead to high chip temperatures. Examples include cars, robots, aircraft and spacecraft. High operating temperatures accelerate the aging of the chips, thus increasing transient and permanent failure rates. Current ways to deal with this mostly turn off the processor core or drastically slow it down when some part of it is seen to exceed a given temperature threshold. However, this pass/fail approach ignores the fact that (a) processors experience accelerated aging due to high temperatures, even if these are below the threshold, and (b) while deadlines are a constraint for real-time tasks to keep the controlled plant in the allowed state space, the actual controller response times that will increase if the voltage or frequency is lowered (to cool down the chip) are what determine the controlled plant performance. Existing approaches also fail to exploit the tradeoff between controller reliability (affected by its temperature history) and the performance of the plant. This project addresses these issues. Load-shaping algorithms are being devised to manage thermal stresses while ensuring appropriate levels of control quality. Such actions include task migration, changing execution speed, selecting an alternative algorithm or software implementation of control functions, and terminating prematurely optional portions of iterative tasks. Validation platforms for this project include automobiles and unmanned aerial vehicles. These platforms have been chosen based on both their importance to society and the significant technical challenges they pose. With CPS becoming ever more important in our lives and businesses, this project which will make CPS controllers more reliable and/or economical has broad potential social and economic impacts. Collaboration with General Motors promotes transition of the new technology to industry. The project includes activities to introduce students to thermal control in computing, in courses spanning high-school, undergraduate and graduate curricula.