Realtime Ray Tracing and Interactive Global Illumination - Scientific ...

List of Figures
2.1 Ray casting . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2 Classical recursive ray tracing . . . . . . . . . . . . . . . . . . 12
2.3 Camera, surface, light, and environment shaders . . . . . . . . 15
5.1 Examples from the Utah Interactive Ray Tracer . . . . . . . . 47
5.2 Examples from the Utah “Star-Ray” cluster ray tracing system 48
5.3 The GPU as a stream processing hardware . . . . . . . . . . . 52
5.4 Examples from Purcell’s ray tracer . . . . . . . . . . . . . . . 54
5.5 Bandwidth reduction in relation to packet size . . . . . . . . . 58
5.6 The SaarCOR benchmark scenes . . . . . . . . . . . . . . . . 59
5.7 Overview of the SaarCOR hardware architecture . . . . . . . . 61
6.1 SIMD data organization . . . . . . . . . . . . . . . . . . . . . 79
6.2 Overhead of 1:4 Traversal . . . . . . . . . . . . . . . . . . . . 84
6.3 Shallower BSPs through SIMD 1:4 intersection . . . . . . . . . 84
6.4 Loss of coherence at the hit points . . . . . . . . . . . . . . . . 87
7.1 Kernel data organization . . . . . . . . . . . . . . . . . . . . . 94
7.2 SoA Layout of the ray packets . . . . . . . . . . . . . . . . . . 98
7.3 Memory organization of BSP nodes . . . . . . . . . . . . . . . 104
7.4 BSP Traversal cases . . . . . . . . . . . . . . . . . . . . . . . . 105
7.5 Surface Area Heuristic vs. Kaplan BSP example . . . . . . . . 113
7.6 Post-process memory optimizations . . . . . . . . . . . . . . . 119
7.7 Basic RTRT benchmarking scenes . . . . . . . . . . . . . . . . 120
7.8 SAH – Getting stuck in local minima . . . . . . . . . . . . . . 121
8.1 RTRT/OpenRT scalability . . . . . . . . . . . . . . . . . . . . 134
9.1 BART example scenes . . . . . . . . . . . . . . . . . . . . . . 143
9.2 The two-level hierarchy used for ray tracing dynamic scenes . 145
9.3 Grouping of triangles into objects for hierarchical animation . 146
9.4 Editing the 12.5 million triangle power plant scene . . . . . . 146