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Technology trends enable the integration of many processor cores in a System-on-Chip (SoC). In these complex architectures, several architectural parameters can be tuned to find the best trade-off in terms of multiple metrics such as energy and delay. The main goal of the MULTICUBE project consists of the definition of an automatic Design Space Exploration framework to support the design of next generation many-core architectures 1 .

Nowadays, owing to unpredictable changes of the environment and workload variation, optimally running multiple applications in terms of quality, performance and power consumption on embedded multi-core platforms is a huge challenge. A lightweight run-time manager, linked with an automated design-time exploration and incorporated in the host processor of the platform, is required to dynamically and efficiently configure the applications according to the available platform resources (e.g. processing elements, memories, communication bandwidth), for minimising the cost (e.g. power consumption), while satisfying the constraints (e.g. deadlines). This study presents a flow linking a design-time design space explorer, coupled with platform simulators at two abstraction levels, with a fast and lightweight priority-based heuristic integrated in the run-time manager to select near-optimal application configurations. To illustrate its feasibility and the very low complexity of the run-time selection, the proposed flow is used to manage the processors and clock frequencies of a multiple-stream MPEG4 encoder chip dedicated to automotive cognitive safety applications

In an MP-SoC environment, a customized run-time management layer should be incorporated on top of the OS kernel to alleviate the run-time decision making and to optimize across all applications several costs (e.g. performance, energy consumption) according to the current environment and the platform resource availabilty. To that end, we propose an extended Pareto-based approach combining a design-time exploration per application with a low-complexity run-time manager. In this paper, a real-life image processing application, simulated on our MP-SoC platform simulator, is used to illustrate the optimal trade-offs offered by the application exploration to the runtime manager, so avoiding conservative worst-case assumptions at design time.