Hardware and embedded for AI applications

Introduction

Modern AI strongly relies on hardware acceleration for both training and inference. Designing and studying to what extent this relation affect the performance, is of a crucial importance

Available Theses

  • Power and energy consumption in AI on hw
  • High level synthesis for ad-doc hardware design​
  • Reliability of hw under stressful AI sessions

Theses In progress

  • None at the moment

Project & Collaborations

In progress

References

  • Carlo Sansone, Full Professor (This email address is being protected from spambots. You need JavaScript enabled to view it.)
  • Stefano Marrone, PhD (This email address is being protected from spambots. You need JavaScript enabled to view it.)