Hai-Chan Li

Energy-Efficient Optimization of Cloud-Native Deep Learning Services for Power Load Forecasting

Power-load forecasting models are increasingly deployed as containerized cloud services. Variable and bursty demand can lead to resource overprovisioning, whereas CPU-based horizontal scaling often reacts too late. We propose PEAS, an energy-aware predictive autoscaler for online power-load forecasting. A GRU forecasts...