Runtime Resource Management Techniques for Many-core Architectures: The 2PARMA Approach

Real-time applications, hard or soft, are raising the challenge of unpredictability. This is an extremely difficult problem in the context of modern, dynamic, multiprocessor platforms which, while providing potentially high performance, make the task of timing prediction extremely difficult. Also, with the growing software content in embedded systems and the diffusion of highly programmable and re-configurable platforms, software is given an unprecedented degree of control on resource utilization. Existing approaches that are looking into Runtime Resource Management (RTRM) still require big design-time efforts, where profiling information is gathered and analyzed in order to construct a runtime scheduler that can be lightweight. There is a trade-off to be made between design-time and runtime efforts. In this paper we present a framework for RTRM on many-core architectures. This RTRM will offer an optimal resource partitioning, an adaptive dynamic data management and an adaptive runtime scheduling of the different application tasks and of the accesses to the data. Furthermore, the 2PARMA RTRM takes into account: i) the requirements/specifications of many-core architectures, applications and design techniques; ii) OS support for resource management and iii) a design space exploration phase.