Power minimisation for real-time dataflow applications.

Energy efficient execution of applications is important for many reasons, e.g. time between battery charges, device temperature. Voltage and Frequency Scaling (VFS) enables applications to be run at lower frequencies on hardware resources thereby consuming less power. Real-time applications have deadlines that must be met otherwise their output is devalued. Dataflow modelling of real-time applications enables off-line verification of the application's temporal requirements. In this paper we describe a method to reduce the combined static and dynamic energy consumption using a Dynamic VFS (DVFS) technique for dataflow modelled real-time applications that may be mapped onto multiple hardware resources. We achieve this by using an application's static slack in order to perform DVFS while still satisfying the application's temporal requirements. We show that by formulating a dataflow modelled application and its mapping as a convex optimisation problem, with energy consumption as the objective function, the problem can be solved with a generic convex optimisation solver, producing an energy optimal constant frequency per application task. Our method allows task frequencies to be constrained such that, e.g. one frequency per application or per processor may be achieved.