Offline RL Framework That Dynamically Controls The GPU Clock And Server Fan Speed To Optimize Power Consumption And Computation Time (KAIST)

Offline RL Framework That Dynamically Controls The GPU Clock And Server Fan Speed To Optimize Power Consumption And Computation Time (KAIST)

A new technical paper titled “Power Consumption Optimization of GPU Server With Offline Reinforcement Learning” was published by researchers at Korea Advanced Institute of Science and Technology (KAIST) and KT Research and Development Center. “Optimizing GPU server power consumption is complex due to the interdependence of various components. Conventional methods often involve trade-offs: increasing fan speed enhances cooling but raises overall …