HADA: An automated tool for hardware dimensioning of AI applications

In recent years, the uptake of Artificial Intelligence (AI) in industry is increasing. For many that respects user-defined constraints (e.g., budget, time, solution quality).In the experimental evaluation we validate our approach on a complex problem, namely online algorithms for energy systems, an area characterized by uncertainty and tight HW and real-time constraints. Results show the effectiveness of our approach and its flexibility: We can train the ML models only once and reuse them in the optimization model to tackle a variety of problems, determined by different data instances and user-defined constraints.