Computing systems are more and more ubiquitous, at scales from tiny embedded systems to large-scale cloud infrastructures. They are more and more adaptive and reconfigurable, for resource management, energy efficiency, or by functionality. Furthermore, these systems are increasingly complex and autonomous: their administration cannot any longer rely on a strong interaction with a human administrator. The correct design and implementation of automated control of the reconfigurations and/or their tuning is recognized as a key issue for the effectiveness of these adaptive systems.
Our objective is to build methods and tools for the design of safe controllers for autonomic, adaptive, reconfigurable computing systems. To attain this goal, we propose to combine Computer Science and Control Theory, followinf the axes corresponding to the different levels of of this co-design problem: adaptive systems infrastructures, programming support, and modeling and control techniques. Our team groups complementary competences, from different laboratories, in order to contribute more efficiently to the topic of hardware/softxare interfaces, particularly active locally to Grenoble, and more widely nationally and internationally in the emerging community on Feedback Computing.
We aproach the topic of control for autonomic, adaptive, and reconfigurable computing along three axes:
- Programming language for reconfigurable systems: reactive languages, component-based approaches
- Control techniques: classical, predictive, and discrete control targeted at computing systems;
- Integration within feedback computing platforms design flows : Domain-Specific Languages, reconfigurable infrastructures (software, hardware)