Institute for Communication Technologies and Embedded Systems

Sustainable AI compiler for edge applications in RISC-V and neuromorphic systems


We want to ease the AI model deployment on edge devices via compiler technology. Most frameworks (e.g., micro tensorflow) only allow to target a few devices or yield a large overhead from the runtime. Therefore, a novel and innovative solution is required. Be part of our path towards a more sustainable future of AI and participate in developing an AI compiler for RISC-V and neuromorphic systems.


  • Develop LLVM and MLIR extensions to map AI workloads on edge devices
  • Build a runtime for RISC-V cores to execute ML models
  • Demonstrate real-world applications to solve today's AI challenges


Must have:

  • Good C++ and Python knowledge
  • Interest in computer architectures and compilers