F4 Room

Computing

F4 addresses Landauer’s and Turing’s fundamental limits. It explores novel computing platforms and models to tackle the energy consumption and computability issues of digital systems.

Key Questions

Neuromorphic models, biological platforms, and specialized hardware like SpiNNaker2 and FPGA are needed to reduce energy consumption and latency.

No, alternative models like BSS machines are needed to handle real numbers natively, ensuring trust in the metaverse.

Existing technologies such as SpiNNaker2 and FPGA will be used, alongside automatic design exploration tools for rapid prototyping

Approach

  • Development of CeTI2 platforms for distributed computing and AI.
  • Study of reliable systems to ensure security and privacy, particularly against quantum threats.

Expected Results

  • OpenRAN/5G tasks on neuromorphic hardware + FPGA-based post-quantum prototype.
  • Evaluation of OpenRAN sub-functions on quantum hardware + formal verification methods.
  • Offloading of computing tasks to analogue hardware + comparison with digital platforms.
  • Implementation of formally verified critical hardware components.
  • Quantum-enhanced OpenRAN on heterogeneous platforms.
  • Extension to biological computing to address non-Turing-computable functions.