ComBoost: An Instruction Complexity Aware DTM Technique for Edge Devices

Recent edge devices show high power density in CPUs, resulting in excessive heat generation. Since mechanical cooling solutions are impractical in edge devices due to their small form factor, software-controlled dynamic thermal management (DTM) plays a crucial role in resolving thermal problems. In state-of-the-art edge devices, proactive DTM techniques such as ARM intelligent power allocation (IPA) mainly exploit the current CPU status (e.g., on-chip temperature, core utilization, and frequency) to estimate the current power consumption which eventually affects the future on-chip temperature. However, they overlook the impact of instruction complexity on thermal behaviors, which results in too conservative or aggressive voltage and frequency control. Even with the same frequency and core utilization, the on-chip temperature increases with different gradients depending on the instruction complexity of workloads. In this paper, we propose an instruction complexity aware DTM technique for edge devices, called ComBoost. Based on the real-time monitoring of on-chip temperature, utilization, and frequency, ComBoost examines the instruction complexity as well as the current CPU status to determine the target frequency. ComBoost then proactively adjusts the voltage and frequency of cores to minimize the performance degradation from thermal throttling. In the off-the-shelf edge device, ComBoost improves performance by 16.8%, 18.6%, and 15.5%, on average, compared to the legacy, IPA, and prior RL-based technique, respectively.