ThermE: Predictive Management of Shared Thermal Headroom for Sustained LLM Inference on Thermally Constrained Edge SoCs
ThermE is a runtime system designed to manage shared thermal headroom for continuous Large Language Model (LLM) inference on compact edge System-on-Chips (SoCs). It works by predicting how different workloads affect shared heat, using physics-informed neural networks to estimate future thermal capacity. This allows the system to proactively adjust operations, balancing serving quality with long-term thermal safety.