Energy-aware scheduling of multi-version tasks on heterogeneous real-time systems

The emergence of battery-powered devices has led to an increase of interest in the energy consumption of computing devices. For embedded systems, dispatching the workload on different computing units enables the optimisation of the overall energy consumption on high-performance heterogeneous platforms. However, to use the full power of heterogeneity, architecture specific binary blocks are required, each with different energy/time trade-offs. Finding a scheduling strategy that minimises the energy consumption, while guaranteeing timing constraints creates new challenges. These challenges can only be met by using the full heterogeneous capacity of the platform (eg heterogeneous CPU, GPU, DVFS, dynamic frequency changes from within an application).