Reducing Peak Power Consumption inMulti-Core Systems without ViolatingReal-Time Constraints

The potential of multi-core chips for high performance and reliability at low cost has made them ideal computing platforms for embedded real-time systems. As a result, power management of a multi-core chip has become an important issue in the design of embedded real-time systems. Most existing approaches have been designed to regulate the behavior of average power consumption, such as minimizing the total energy consumption or the chip temperature. However, little attention has been paid to the worst-case behavior of instantaneous power consumption on a chip, called chip-level peak power consumption, an important design parameter that determines the cost and/or size of chip design/packaging and the underlying power supply. We address this problem by reducing the chip-level peak power consumption at design time without violating any real-time constraints. We achieve this by carefully scheduling real-time tasks, without relying on any additional hardware implementation for power management, such as dynamic voltage and frequency scaling. Specifically, we propose a new scheduling algorithm FP
_Θ
that restricts the concurrent execution of tasks assigned on different cores, and perform its schedulability analysis. Using this analysis, we develop a method that finds a set of concurrent executable tasks, such that the design-time chip-level peak power consumption is minimized and all timing requirements are met. We demonstrate via simulation that the proposed method not only keeps the design-time chip-level peak power consumption as low as the theoretical lower bound for trivial cases, but also reduces the peak power consumption for non-trivial cases by up to 12.9 percent compared to the case of no restriction on concurrent task execution.