Jihun Yun, Aurelie Lozano, et al.
NeurIPS 2021
Rapid growth of the world-wide Information Technology (IT) infrastructure fueled by demands of the global Digital Economy and associated demands for electrical power creates significant impact on the environment. Over the past decade power usage effectiveness (PUE) was the major focus for improving energy efficiency of Data Centres in particular. While PUE did result in significant energy efficiency improvements, it is not sufficient by itself. Huge energy efficiency gains are expected from optimizing hardware utilization, cooling and software stacks. We present an AI-Driven Holistic Approach to energy and power management in data centres, which can be described as Energy Aware Scheduling (EAS). EAS uses AI-driven workloads aware software-hardware co-design to optimize energy efficiency of a data centre.
Jihun Yun, Aurelie Lozano, et al.
NeurIPS 2021
Imran Nasim, Michael E. Henderson
Mathematics
Ge Gao, Xi Yang, et al.
AAAI 2024
Daniele Lotito
Dynamical Systems in Lecce 2025