Improving TAS Adaptability with a Variable Temperature Threshold

Thermal-Aware Scheduling (TAS) provides methods to manage the thermal dissipation of a computing chip during task execution. These methods aim to avoid issues such as accelerated aging of the device, premature failure and degraded chip performance. In this work, we implement a new TAS algorithm, VTF-TAS, which makes use of a variable temperature threshold to control task execution and thermal dissipation. To enable adequate execution of the tasks to reach their deadlines, this threshold is managed based on the theory of fluid scheduling. Using an evaluation methodology as described in POD-TAS, we evaluate VTF-TAS using a set of 4 benchmarks from the COMBS benchmark suite to examine its ability to minimize chip temperature throughout schedule execution. Through our evaluation, we demonstrate that this new algorithm is able to adaptively manage the temperature threshold such that the peak temperature during schedule execution is lower than POD-TAS, with no requirement for an expensive search procedure to obtain an optimal threshold for scheduling.