An Investigation into Power Aware Aspects of Rendering 3D Models on Multi-Core Processors

Abstract

Graphics Processing Units (GPUs) are designed to process numerically intensive applications and specially customized with additional computational power to achieve efficient rendering of 3D applications. Shaders are basically the computer programs that run on graphics rendering pipeline and inform about how to process and render each pixel, to perform efficient rendering of 3D applications. Shaders included in our Geometric complexity, texture resolution, per-pixel lighting. These shaders expose GPUs to suffer more power utilization during rendering process. In this paper, initially GPU power usage is investigated at run-time for rendering configuration to define shader parameters on a 3D scene and then power prediction model is proposed at different shader calls on GPU to generate power-aware dynamically reconfigurable rendering model. In the implementation process we integrate the TensorFlow management library routines and dynamic voltage and frequency scheduling (DVFS) mechanism to improve efficiency in rendering process and reach optimal power savings. To analyze the power efficiency of GPUs, shader parameters such as geometric complexity, texture resolution, per-pixel lighting, filtering that expose more towards power consumption are experimented with common GPU workloads during rendering process, then frequency and voltage is altered based on the framerate monitoring. Also in addition to this the frame rate is monitored and maintained in such a way that GPU frequency is adjusted in parallel if the framerate is within the acceptable range so that unnecessary power usage is reduced. During the experimental tests a lower limit of 30 frames per second and upper limit of 60 frames per second is configured. The GPU frequency is reduced if the existing framerate is greater than upper configured limit and frequency range is increased if framerate is below the configured lower limit. Compared with the previous state of art, results show power savings around 40% and improved speedup in computation time with maximum quality of a 3D scene.