An Interplay of Energy and Temperature Minimization Techniques for Heterogeneous Multiprocessor Systems
Yanshul Sharma, Swati Gupta, Sanjay Moulik · 2023
Real-time embedded systems are designed to perform specific functions in real-time, with a microcontroller, memory, and input/output devices. The scheduler is a critical component that manages resource allocation and schedules jobs based on priority and available resources. Multiprocessor platforms improve performance, scalability, redundancy, and flexibility, with different approaches to scheduling, such as global, partitioned, and semi-partitioned. Minimizing dynamic energy consumption and processor temperatures is essential for improving battery life and reliability and meeting power and thermal constraints in applications such as mobile devices, aerospace, and defense systems. There are many energy and temperature management techniques, but their effect on each other has not been studied in detail. Hence, we want to employ a few of those techniques and want to observe their impacts. In this work, we first propose a basic semi-partitioned scheduler for heterogeneous multiprocessor systems which supports the execution of real-time jobs. Then, we apply well-known energy and temperature minimization techniques over the proposed scheduler to study their impact on the system. To conduct our experiments, we use benchmark programs whose characteristics have been extracted using various simulators.