Proposals need to address:
- The design of innovative and energy-efficient processing solutions for AI on theedge and deep-edge, with a focus on new processor architectures and middleware.
- Tools allowing semi-automatic and automatic design space exploration, including variants of algorithms, computing paradigms, hardware performances, energy efficiency, etc.
- Scalable architecture, use of interposer and chiplets to build chips for various applications (for edge and for embedded HPC applications) with the same family of hardware building blocks with efficient interconnection network, e.g. using photonics.
- Development of hybrid architectures, integration and cooperation of neuromorphic or other non-conventional computing solutions within classical systems. Supporting design tool chains and OSs addressing multiple computing paradigms
- Middleware and engineering tools, to reach a trade-off between training cost, power consumption and execution time while supporting virtualization concepts.
- Advanced memory management
- Automated transfer-learning, meta-learning, and real-time learning at the edge
- Secure (i.e. trustworthy and explainable) edge-AI by design.
- Encouraging SMEs to participate in those developments, in particular paying attention to the needs of SMEs, involve SMEs in project execution, and develop solutions that can be taken up and/or exploited by SMEs