Application- and platform-agnostic runtime power management of heterogeneous embedded systems

Increasing energy efficiency and reliability at runtime is a key challenge of heterogeneous many-core systems. We demonstrate how contributions from the PRiME project integrate to enable application- and platform-agnostic runtime management that respects application performance targets. We consider opportunities to enable runtime management across the system stack and we enable cross-layer interactions to trade-off power and reliability with performance and accuracy. We consider a system as three distinct layers, with abstracted communication between them, which enables the direct comparison of different approaches, without requiring specific application or platform knowledge. Application-agnostic runtime management is demonstrated with a selection of runtime managers from PRiME, including linear regression modelling and predictive thermal management, operating across multiple applications. Platform-independent runtime management is demonstrated using two heterogeneous platforms.