1 / 21

GPU

GPU Graphics Processing Unit Graphics Pipeline Scene Transformations Lighting & Shading Viewing Transformations GPUs evolved as hardware and software algorithms evolve Rasterization Early Graphics Originally, no specialized graphics hardware All processing in software on CPU,

Gabriel
Télécharger la présentation

GPU

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. GPU • Graphics Processing Unit

  2. Graphics Pipeline Scene Transformations Lighting & Shading Viewing Transformations GPUs evolved as hardware and software algorithms evolve Rasterization

  3. Early Graphics • Originally, no specialized graphics hardware • All processing in software on CPU, • Results transmitted to frame buffer • first, external frame buffers • later, internal frame buffers. CPU Frame buffer Display

  4. Geometry data Transform & lighting Culling, perspective divide, viewport mapping Rasterization Simple texturing Depth test Frame buffer blending More detailed pipeline Simple functionality transferred to specialized hardware.

  5. Geometry data Transform & lighting Culling, perspective divide, viewport mapping Rasterization Simple texturing Depth test Frame buffer blending Add more functionality to GPU. Simple functionality transferred to specialized hardware

  6. Fixed function GPU pipeline Scene Transformations • Pipeline implemented in hardware • Each stage does fixed task • Tasks are parameterized • Inflexible – fixed, parameterized functions • Vector-matrix operations (some parallelism). Lighting & Shading Viewing Transformations GPU CPU Display Rasterization Frame buffer

  7. Technology advances • Hardware gets cheaper, smaller, and more powerful • Parallel architectures develop • Graphics processing get more sophisticated (environmental mapping, displacement mapping, sub-surface scattering) • Need more flexibility in GPUs.

  8. Geometry data Transform & lighting Culling, perspective divide, viewport mapping Rasterization Complex texturing Depth test, alpha test, stencil test Frame buffer blending Make this programmable:Vertex Shader Make this programmable: Fragment Shader

  9. Vertex shader • Graphics systems: convert everything to triangles • Pass vertices, normals, colors, texture coordinates to GPU processor • GPU: vertex-based computations, • Independent of other vertices • Later, assemble into triangles.

  10. Fragment shader • Fragment is triangle clipped to pixel • Interpolate values • Multiple textures, Alpha, stencil, depth • Independent of other fragments • Blend with contents of frame buffer.

  11. Geometry data Vertex Shader Vertex Shader Vertex Shader Culling, perspective divide, viewport mapping Introduce parallelism: add multiple units Rasterization Fragment Shader Fragment Shader Fragment Shader Alpha test, depth test, stencil test Frame buffer blending

  12. Shading language • Shade trees -> Pixar’s Renderman shader

  13. Shader Language • Low level (like assembler) but high-level language compilers: nVidia’s Cg • 4 component floating point data type • SIMD

  14. Cg: C-based graphics program • Array & structures • Flow control • Vectors & matrices • No memory allocation, file I/O

  15. Power • GPUs have moved away from the traditional fixed-function 3D graphics pipeline toward a flexible general-purpose computational engine. • The raw computational power of a GPU dwarfs that of the most powerful CPU, and the gap is steadily widening. • GPUs have moved away from the traditional fixed-function 3D graphics pipeline toward a flexible general-purpose computational engine

  16. Next: unify shaders • One set of shaders • Allocate to either vertices or fragments

  17. Pipeline evolved

  18. Evolved pipeline

  19. GPGPU • Make GPU more general – adapt certain types of programs to it’s pipelined, parallel architecture • Single GeForce 8800 chip achieves a sustained 330 billion floating-point operations per second (Gflops) on simple benchmarks • Cost-effective: graphics driving demand up, supply up, price down for GPUs • Finding uses in non-graphics applications.

  20. GeForce 8800 GTX

  21. More general: NVIDIA’s CUDA • More general data parallel model • Decompose across threads • Sharing and communication between threads..

More Related