High-performance adaptive texture streaming and rendering of large 3D cities

Abstract

We propose a high-performance texture streaming system for real-time rendering of large 3D cities with millions of textures. Our main contribution is a texture streaming system that automatically adjusts the streaming workload at runtime based on measured frame latencies, specifically addressing the high memory binding costs of hardware virtual texturing which causes frame rate stuttering. Our system streams textures in parallel with prioritization based on GPU computed mesh perceptibility, and these textures are cached in a sparse partially resident image at runtime without the need for a texture preprocessing step. In addition, we improve rendering quality by minimizing texture pop-in artifacts using a color blending scheme based on mipmap levels. We evaluate our texture streaming system using three structurally distinct datasets with many textures and compared it to a baseline, a game engine, and our prior method. Results show an 8X improvement in rendering performance and 7X improvement in rendering quality compared to the baseline.

GPU Shader Analysis and Power Optimization Model

“…But higher clock frequencies often require higher voltage levels, resulting in increased power consumption [3,4,10]. To enhance both speed and the quality of rendering, while considering the significance of textures and geometry, cutting-edge, highperformance texture streaming systems have been developed [11,12]. The power consumption in shaders is influenced by a combination of factors related to the complexity of the shader code, the number of shader invocations, and memory access patterns.…”