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Emerging multi/many-core architectures, targeting both High Performance Computing (HPC) and mobile devices, increase the interest for self-adaptive systems, where both applications and computational resources could smoothly adapt to the changing of the working conditions. In these scenarios, an efﬁcient Run-Time Resource Manager (RTRM) framework can provide a valuable support to identify the optimal tradeoff between the Quality-of-Service (QoS) requirements of the applications and the time varying resources availability.
This paper introduces a new approach to the development of a system-wide RTRM featuring: a) a hierarchical and distributed control, b) the exploitation of design-time information, c) a rich multi-objective optimization strategy and d) a portable and modular design based on a set of tunable policies. The framework is already available as an Open Source project, targeting a NUMA architecture and a new generation multi/many-core research platform. First tests show beneﬁts for the execution of parallel applications, the scalability of the proposed multiobjective resources partitioning strategy, and the sustainability of the overheads introduced by the framework.