A Data-Traffic Aware Dynamic Power Management for General-Purpose Graphics Processing Units

General-purpose graphics processing units (GPGPUs) are gaining popularity. Applications like machine learning and artificial intelligence have been growing rapidly. When hardware complexity increases to meet the computing requirements of the applications, the power efficiency of the hardware becomes an important issue. In this paper, we propose an adaptive power management scheme for GPGPU to enhance power efficiency by proactively detecting the internal activities during runtime and dynamically adjusting the operating frequencies of selected components. The simulation results indicate that, when compared with the baseline approach, the proposed scheme can reduce power consumption by up to 15% with a performance overhead of less than 5% on average.