Wolfgang Hillen Summer School 2020

Modeling and Design of Next Generation Self-X MPSoC Platforms

July 27 – July 31, 2020 - postponed into Winter 2020/21 or Summer 2021 (new Date tba) 
UC Irvine, California, USA

With the recent successful developments in artificial intelligence, several research activities are being carried out to bring self-X properties (as self-adaptivity, self-awareness, self-organization, self-healing, etc.) to embedded systems, leading the path toward smart embedded systems. One key step is to abstract the complexity of enabling self-X properties into a model allowing the control and steering of a system’s dynamics at runtime, to enable these self-X features.

For that purpose, we, partners from California (UC Irvine), Bavaria (TU München), and Lower Saxony (TU Braunschweig), have proposed a model called the “Information Processing Factory” (IPF) that aims to show how these self-X properties can be achieved across multiple abstraction levels of a Multi-Processor System-on-Chip (MPSoC) platform. The IPF idea comes from the similarities between microelectronics systems and factories: all the components have to adapt to the current workload. In a factory, a department or manufacturing group is given a target production rate objective as well as firm constraints on the utilities to use, such as electricity, source materials, and monetary production cost per unit. The department or group has a maximum of freedom on how to accomplish these targets under the constraints. At the same time, the produced goods of a given group are not as critical as other critical goods for the success of the factory as a whole. However, assuming that a given performance target can be achieved with different amounts of resources occupied, finding an approach to satisfy the objective target with the minimum amount of resources (i.e., having identified a Pareto point) frees up resources and utilities that may be used to optimize the critical production processes.

With IPF, we are therefore defining a shift of paradigm in system design by envisioning the move toward a platform-centric design in which the combination of self-organized learning and formal reactive methods guarantee the applicability of self-X systems in safety-critical and high-availability applications.

This year‘s summer school wants to share the finding of IPF in an interactive and practical manner with three goals in mind:

  • Since IPF includes novel concepts with specific models for concrete problems, they will be formally described so that participants clearly understand the research questions and how they are tackled. This is given in the form of a lecture series.

  • Capitalizing on the multi-disciplinary background of the different research groups (electrical engineering, computer science, and mathematics), the Summer School offers different points of view on how approaches from different research areas are used in IPF and how their synergy contributes to the project’s success. This is given in the form of seminar talks.

  • With the obtained results in IPF, the summer school gives the opportunity to participants to get hands-on experience with different techniques that enable self-X features on embedded systems. This is achieved in workshops, where participates tackle micro research topics with a clear goal in mind.

 

Call for Contribution

We are inviting master and PhD students from various degree programs to submit their application according to the following guidelines.

Submission Guidelines

All applications must contain a one-page description in IEEE conference format of your experience and/or interest in the field of self-x MPSoC platforms. It also has to contain a discussion about advantages and disadvantages of self-X mechanisms.
Furthermore, we request a CV and a recent transcript of records.

To gain deeper insight about self-X properties in our IPF project you find some of our recent publications at IEEE and ACM:

  • https://ieeexplore.ieee.org/abstract/document/8466995
    M. Möstl et al., "Platform-Centric Self-Awareness as a Key Enabler for Controlling Changes in CPS," in Proceedings of the IEEE, vol. 106, no. 9, pp. 1543-1567, Sept. 2018.

  • https://ieeexplore.ieee.org/abstract/document/8949899
    E. A. Rambo et al., "The Information Processing Factory: A Paradigm for Life Cycle Management of Dependable Systems," 2019 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS), New York, NY, USA, 2019, pp. 1-10.

  • https://dl.acm.org/doi/abs/10.1145/3352460.3358312
    Bryan Donyanavard et al., “SOSA: Self-Optimizing Learning with Self-Adaptive Control for Hierarchical System-on-Chip Management” in Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO ’52), Columbus, OH, USA, 2019, pp 685–698.

Submission Deadline: April 17, 2020 (still open - extended as new date tba)

Despite the current uncertainties and governmental travel restrictions in connection to COVID-19 we encourage all interested students to apply for this summer school by the indicated application deadline. We will do our best to stick to the above described plans and schedule.
Update 21.04.2020: Due to the current situation caused by COVID-19, we have to postpone the summer school. A new date including a new application deadline will be announced soon.

Data Protection Information

Regarding the processing of personal data we refer to: https://portal.mytum.de/kompass/datenschutz/Bewerbung/

All points apply accordingly for the summer school organized by TUM and UCI.

Support

For a limited number of candidates we have the opportunity to support their flights. Furthermore, we help finding a place to stay at UCI for German applicants.

Venue

The 2020 Wolfgang Hillen Summer School will be held at the University of California, Irvine (UCI).

Contact

Submissions and questions about submissions should be emailed to flo.maurer@tum.de.

Organizers

Prof. Andreas Herkersdorf (LIS ,TUM), Prof. Fadi Kurdahi (CECS, UCI), Prof. Nikil Dutt (CECS, UCI)

Sponsor

We like to thank for the financial support by the Bavaria California Technology Center (BaCaTeC).