Thermal-Aware Task Assignment for Real-Time Applications on Multi-Core Systems

Abstract

The reduced feature size of electronic systems and the demand for high performance lead to increased power densities and high chip temperatures, which in turn reduce the system reliability. Thermal-aware task allocation and scheduling algorithms are promising approaches to reduce the peak temperature of multi-core systems with real-time constraints. However, as long as the worst-case chip temperature is not incorporated into system analysis, no guarantees on the performance can be given. This paper explores thermal-aware task assignment strategies for real-time applications with non-deterministic workload that are running on a multi-core system. In particular, tasks are assigned to the multi-core system so that the worst-case chip temperature is minimized and all real-time deadlines are met. Each core has its own clock domain and the static assigned frequency corresponds to the minimum operation frequency such that no real-time deadline is missed. Finally, we show that the proposed temperature minimization problem can efficiently be solved by metaheuristics.