ProjectMANNHEIM-FlexKI – Flexible AI deployment and AI platforms for embedded automotive applications

Basic data

Flexible AI deployment and AI platforms for embedded automotive applications
01/09/2022 to 31/08/2025
Abstract / short description:
The project FlexKI aims to break the hardware dependency of current development processes for AI applications and to explore an open reference approach for the deployment of AI and DSP applications. Two development paths are considered: 1) The flexible deployment of networked AI applications on high-performance, heterogeneous off-the-shelf hardware platforms. 2) A hardware/software co-design approach for deployment onto a new customized, energy-efficient AI hardware platform. Both development paths avoid vendor lock-in, enable fast and automatic migration of AI applications to alternative hardware platforms in the case of unavailability of specific hardware components due to protectionism, blacklisting or supply bottlenecks (chip crisis). The project strengthens all levels of the automotive value chain in Germany and establishes a path for standardization in the field of AI deployment. The contribution of the University of Tübingen aims to enable efficient and automated mapping of AI applications onto hardware platforms containing heterogeneous hardware accelerators as well as the optimization of the whole hardware platform and the automated mapping of networked AI/DSP applications.
machine learning
maschinelles Lernen
Automatisiertes Fahren

Involved staff


Faculty of Science
University of Tübingen
Wilhelm Schickard Institute of Computer Science (WSI)
Department of Informatics, Faculty of Science

Local organizational units

Department of Informatics
Faculty of Science
University of Tübingen


Bonn, Nordrhein-Westfalen, Germany

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