On-the-fly energy minimization for multi-mode real-time systems on heterogeneous platforms

The increasing computational demands of next generation multimedia systems require innovative optimization methods. Modern heterogeneous architectures bring together multiple general-purpose CPUs and multiple GPUs and FPGAs, in an attempt to answer the performance, energy-efficiency and flexibility requirements of today's complex multimedia applications. However, in order to leverage the advantages of such architectures, careful optimization is essential. In modern systems, more and more multimedia applications need real-time support (e.g. automotive systems that use image processing for active safety features). Real-time multi-mode systems are a good model for a wide range of applications that dynamically change their computational requirements over time. In this context, intelligent on-line resource management is needed, such that the heterogeneous resources are used in an energy-efficient manner, while meeting the real-time constraints. This paper proposes a resource manager that implements run-time policies to decide on-the-fly task admission and the mapping of active tasks to resources, such that the energy consumption of the system is minimized and all task deadlines are met.