Perception-Oriented 3D Rendering Approximation for Modern Graphics Processors

Anisotropic filtering enabled by modern rasterization-based GPUs provides users with extremely authentic visualization experience, but significantly limits the performance and energy efficiency of 3D rendering process due to its large texture data requirement. To improve 3D rendering efficiency, we build a bridge between anisotropic filtering process and human visual system by analyzing users’ perception on image quality. We discover that anisotropic filtering does not impact user perceived image quality on every pixel. This motives us to approximate the anisotropic filtering process for non-perceivable pixels in order to improve the overall 3D rendering performance without damaging user experience. To achieve this goal, we propose a perceptionoriented runtime approximation model for 3D rendering by leveraging the inner-relationship between anisotropic and isotropic filtering. We also provide a low-cost texture unit design for enabling this approximation. Extensive evaluation on modern 3D games demonstrates that, under a conservative tuning point, our design achieves a significant average speedup of 17% for the overall 3D rendering along with 11% total GPU energy reduction, without visible image quality loss from users’ perception. It also reduces the texture filtering latency by an average of 29%. Additionally, it creates a unique perception-based tuning space for performance-quality tradeoffs on graphics processors.