In simpler terms, this project explores how to make high-performance computing servers and data centers smarter using machine learning. By applying advanced algorithms, the team aims to optimize the use of resources in these environments efficiently. Ultimately, the goal is to improve the performance and reliability of these systems while ensuring they operate in a cost-effective and sustainable manner, contributing to advancements in cloud infrastructure management and data center operations.

The project on machine learning for HPC servers and data centers at the ESL lab focuses on utilizing machine learning-based approaches for multi-objective resource management. This research line aims to enhance the efficiency of heterogeneous High Performance Computing (HPC) servers and data centers by employing system-level resource management techniques.