An ILP formulation for task scheduling on heterogeneous chip multiprocessors

One of the main difficuties to map an embedded application onto a multiprocessor architecture is that there are multiple ways of this mapping due to several constraints. In this paper, we present an Integer Linear Programming based framework that maps a given application (represented as a task graph) onto a Heterogeneous Chip Multiprocessor architecture. Our framework can be used with several objective functions such as energy, performance, and fallibility (opposite of reliability). We use Dynamic Voltage Scaling (DVS) for reducing energy consumption while we employ task duplication to minimize fallibility. Our experimental results show that over 50% improvements on energy consumption are possible by using DVS, and the fully task duplicated schedules can be achieved under tight performance and energy bounds.