The collaborative research center SFB876 brings together data mining and embedded systems. On the one hand, embedded systems can be further improved using machine learning. On the other hand, data mining algorithms can be realized in hardware, e.g. FPGAs, or run on GPGPUs. The restrictions of ubiquitous systems in computing power, memory, and energy demand new algorithms for known learning tasks. These resource bounded learning algorithms may also be applied on extremely large data bases on servers.
Prof. Jian-Jia Chen (Principle Investigator of sub-projects A1 and A3 in SFB876) receives the ERC (European Research Council) Consolidator Award 2019 for his project "PropRT - Property-Based Modulable Timing Analysis and Optimization for Complex Cyber-Physical Real-Time Systems.” The grant is about 2 Million Euros for a period of 5 years. Prof. Chen expressed that, “It is my honor to be granted with the ERC Consolidator Award.”
PropRT will explore the possibilities to construct timing analysis for complex cyber-physical real-time systems from formal properties. The target properties should be modular so that safe and tight analysis as well as optimization can be performed (semi-)automatically. New, mathematical, modulable, and fundamental properties for property-based (schedulability) timing analyses and scheduling optimizations are needed to capture the pivotal properties of cyber-physical real-time systems, and thus enable mathematical and algorithmic research on the topic. Different flexibility and tradeoff options to achieve real-time guarantees should be provided in a modularized manner to enable tradeoffs between execution efficiency and timing predictability.
Part of the preliminary results of the project were supported in the scope of SFB876.
