Embedded storage elements on next MCU generation ready for AI on the edge




Principal Investigator:

Jan Komorowski


Uppsala universitet

Start Date:


End Date:


Primary Classification:

10299: Other Computer and Information Science



  • Castor /proj at UPPMAX: 5000 GiB
  • Castor /proj/nobackup at UPPMAX: 5000 GiB
  • Cygnus /proj at UPPMAX: 5000 GiB
  • Cygnus /proj/nobackup at UPPMAX: 5000 GiB
  • Bianca at UPPMAX: 2 x 1000 core-h/month


Artificial Intelligence (AI) is now being used in an ever-growing range of applications, already considered as a key enabling technology for electronic component and systems, representing a potential major business disrupter. It is already put in many applications and brings tangible solutions in many societal challenges. Europe is at the forefront of the Electronic Components and Systems (ECS) at the edge market and related technologies (FD-SOI, eNVM, Imagers, Mems, Sensors, ...). There are big players (pro-riders’ surfers of the illustration, on the left side) in Europe selling Microcontrollers, Sensors, Communication devices, several tens of billion units per year! Numerous European SMEs and start-ups demonstrated innovative systems based on these components. Clearly, Europe is trusting top ranking positions for ECS at the edge definition, development, production and application. The next step is ECS at the edge with AI enablement. storAIge will increase AI technology maturity and capitalize on ‘the ones’ who already have competences and insights to push one step up the full European eco-system and stay on/trust podiums. Our task in this very large European Union and Vinova-financed project (StorAIge – ECSEL-IA-2020) is the application of machine learning to support autonomous medical diagnosis by patient's bed and intelligent tools in the tooling industry.