Thermal-Aware Task Allocation and Scheduling for Embedded Systems

TL;DR

This paper introduces a novel thermal-aware task allocation and scheduling algorithm for embedded systems that reduces peak temperature and balances thermal distribution, improving reliability and performance.

Contribution

It presents the first task scheduling algorithm that explicitly considers temperature, integrating thermal management into hardware/software co-synthesis for embedded systems.

Findings

Thermal-aware approach reduces maximum temperature more effectively than power-aware schemes.

The algorithm achieves a thermally balanced distribution while meeting real-time constraints.

Experimental results demonstrate significant temperature reductions.

Abstract

Temperature affects not only the reliability but also the performance, power, and cost of the embedded system. This paper proposes a thermal-aware task allocation and scheduling algorithm for embedded systems. The algorithm is used as a sub-routine for hardware/software co-synthesis to reduce the peak temperature and achieve a thermally even distribution while meeting real time constraints. The paper investigates both power-aware and thermal-aware approaches to task allocation and scheduling. The experimental results show that the thermal-aware approach outperforms the power-aware schemes in terms of maximal and average temperature reductions. To the best of our knowledge, this is the first task allocation and scheduling algorithm that takes temperature into consideration.