A lightweight software-based runtime temperature monitoring model for multiprocessor embedded systems

Abstract

High-thermal variation and temperature operation can have a noteworthy impact on system performance, power consumption and reliability, which is a major and increasingly critical design metric in emerging multiprocessor embedded systems. Existing thermal management techniques rely on physical sensors to provide them with temperature figures to regulate the system's operating temperature and thermal variation at runtime. However, on-chip thermal sensors present limitations (e.g. extra power and area cost), which may restrict their use in large scale systems. In this regard, this paper proposes a lightweight software-based runtime temperature model, enabling to capture detailed temperature distribution information of multiprocessor systems at a negligible overhead. To validate the proposal, the model is embedded in a distributed-memory MPSoC platform described in RTL. Further, results show that the average absolute error of the temperature estimation, compared to HotSpot is smaller than 4% in systems with up to 36 processing elements.