Improving TAS Adaptability with a Variable Temperature Threshold

TL;DR

This paper introduces VTF-TAS, a thermal-aware scheduling algorithm with a variable temperature threshold that adaptively manages chip temperature, improving thermal regulation without costly optimization procedures.

Contribution

The paper presents a novel TAS algorithm using a variable temperature threshold based on fluid scheduling theory, enhancing thermal management efficiency.

Findings

VTF-TAS achieves lower peak temperatures than POD-TAS.

It adaptively manages temperature thresholds without expensive search procedures.

The algorithm effectively maintains task deadlines while reducing thermal stress.

Abstract

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.