A Machine Learning Approach to Estimating Energy Use in Language Model Inference
The rapid expansion of Large Language Model (LLM) serving in cloud data centers has created a critical need for energy-aware scheduling. However, estimating inference energy typically requires hardware-level power telemetry, which is rarely accessible to cloud tenants. This paper proposes a lightweight, machine-learnin...