1. Ray Tracing on Programmable Graphics Hardware
SIGGRAPH 2002
Timothy J. Purcell Ian Buck
William R. Mark Pat Hanrahan
Sungbae Kim
Master Student in CS

2. Contributions Abstract streaming graphics processor
Implement ray tracing using GPU
Help guide the design of future architectures

3. Why ray tracing?
Ray tracing for the movie “Cars”

4. Ray tracing pros and cons
Good quality
Simple algorithm
Expensive cost
 How to accelerate ray tracing

5. Basic Ray tracing algorithm
Shoot eye rays
Find the first intersection
Calculates the illumination
Reflection? Calls itself
Transmission? Calls itself
Combines the resulting illumination

6. Note that each pixel is independent
Basic Ray tracing ? =
RayTrace( ) = Shade( ) + refl1*RayTrace( )
RayTrace( ) = Shade( ) + refl2*RayTrace( ) +
refr2*RayTrace( ) …
Note that each pixel is independent

7. Find intersection

8. Uniform Grid

9. How to accelerate Many algorithms Use parallel systems
Massively parallel shared memory supercomputer : *-ray
Cluster of commodity PCs : RTRT
Special hardware for ray tracing
Streaming Programming Model : this paper’s approach

10. Streaming Programming Model
A stream is a set of data records
Kernels operate on each element of an input stream independently
Kernels can read from global memory
Streams connect kernels

11. Streaming Ray Tracer Eye Ray Generator Traverser Intersector Shader
Screen Pixels
Eye Ray
Generator
Camera
Rays
Traverser
Grid
(Ray, Voxel)
It is a result of our desire to eventually run the ray tracer on a GPU which lack branching within a fragment program
Intersector
Triangles
Hits
Materials
Shader
Pixel color updates

12. Programmable Graphics Processor Abstraction
We can use GPU as Streaming Processor
But limited streaming processor

13. GPU Ray Tracer Limited  How to map Global Memory
Kernel to Kernel connection
No loop, No branch
It is a result of our desire to eventually run the ray tracer on a GPU which lack branching within a fragment program

14. Texture Memory Mapping
We can use texture as global memory
Store non-RGB values in textures
For example,
The Second triangle of the second grind
Also Rays, Materials

15. Kernel to Kernel
Copy output fragments into Texture

16. No loop No Branch Multipass – operate again until every is done
bodyfp();
} while ( donefp() );
State : z-value, stencil bit
For performance : early z-culling, stencil mask

17. Simulation Result SIMD vs. MIMD
Horizontal line represents the performance of a graphics card when the author researched.
As you see, MIMD structure is better. It means if graphics cards support MIMD structure, ray tracing will be very fast. In
right charts show that in MIMD structure compute bandwidth is more important.

18. GPU vs. CPU Comparable to CPU Radeon 9700 Pro CPU
Ray-triangle intersections/s
100M
20M in P3 800 MHz
Ray/s
300K to 4.0M
800K to 7.1M
1.8M to 2.3M (With simple shading)
in P4 2.5 GHz
Comparable to CPU

19. GPU vs. CPU
Graphics processor evolves faster

20. Demo Shadow rays 10.5 fps Eye rays, Shadow rays, Reflection rays

21. Appendix: General Purpose GPU(GPGPU)
GPU, Shader, GLSL, HLSL, Cg, OpenGL, Direct3D….
BrookGPU (Stanford)
CUDA (NVIDIA)
There is a research area to use GPU in non-graphics area.

22. Appendix: Cell Processor
IBM, SONY, TOSHIBA
Interactive ray tracer : iRT
More faster than GPU