Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

GPU - Basic Working

Basic Working of a GPU, and a comparison with CPU

  • Login to see the comments

GPU - Basic Working

  1. 1. By, Nived R MEC, Cochin
  2. 2. Contents Introduction Need for a GPU CPU vs GPU Components of a GPU GPU Pipeline Future Advancements Applications Conclusion
  3. 3. Introduction A dedicated parallel processor optimized for accelerating graphical computations. Like the CPU (Central Processing Unit), it is a single-chip processor.
  4. 4. Need for a GPU To provide a separate dedicated graphics resources including a graphics processor and memory. To relieve some of the burden of the main system resources.
  5. 5. Offloading compute-intensive portions of the application to the GPU
  6. 6. GPU vs CPU
  7. 7. GPU - highly parallel operation GPU has many execution units GPU has faster memory interfaces as they need to shift around a large amount of data. GPUs have much deeper pipelines GPU vs CPU CPU executes programs serially. CPU has fewer execution units
  8. 8. GPU vs CPU Architecture
  9. 9. WITHOUT GPU WITH GPU
  10. 10. Components of a GPU ❖ Graphics Processor Mainly 2 configurations: ○ Graphics coprocessor : Independent of CPU ○ Graphics accelerator: Based on Commands from CPU
  11. 11. Components of a GPU ❖ Memory: Dual ported memory ❖ Graphics BIOS ❖ Digital-to-Analog Converter (DAC) ❖ Display Connector: VGA connector ❖ Computer (Bus) Connector: AGP
  12. 12. GPU Pipeline The GPU receives geometry information from the CPU as an input and provides a picture as an output.
  13. 13. Input assembler stage This stage is the communication bridge between the CPU and the GPU. It receives commands from the CPU and also pulls geometry information from system memory. It outputs a stream of vertices in object space with all their associated information.
  14. 14. Vertex Processing The vertex-shader stage processes vertices, typically performing operations such as transformations, skinning, and lighting. A vertex shader always takes a single input vertex and produces a single output vertex.
  15. 15. Triangle Setup In this stage geometry information becomes raster information (screen space geometry is the input, pixels are the output)
  16. 16. Triangle Setup (Contd…) Prior to rasterization, triangles that are backfacing or are located outside the viewing frustum are rejected. The rasterizer clips primitives, prepares primitives for the pixel shader, and determines how to invoke pixel shaders. A pixel is generated if and only if its center is inside the triangle
  17. 17. Pixel Processing Each pixel provided by triangle setup is fed into pixel processing as a set of attributes which are used to compute the final color for this pixel The computations taking place here include texture mapping and math operations
  18. 18. Output Merger Stage The output-merger stage combines various types of output data (pixel shader values, depth and stencil information) to generate the final pipeline result.
  19. 19. Programmability in GPU Pipeline In current state of the art GPUs, vertex and pixel processing are now programmable The programmer can write programs that are executed for every vertex as well as for every pixel This allows fully customizable geometry and shading effects that go well beyond the generic look and feel of older 3D applications
  20. 20. Looking Forward Bigger and faster (more cores, more FLOPS) – 2 TFLOPs today, and counting Addition of (select) CPU-like features – More traditional caches Tight integration with CPUs (CPU+GPU hybrids). Completely programmable hardware.
  21. 21. Applications
  22. 22. Shading Structures
  23. 23. Global Illumination
  24. 24. Conclusion ● Graphics Processing Unit is not a wonder that this piece of hardware is often referred to as an exotic product as far as computer peripherals are concerned. ● By observing the current pace at which work is going on in developing GPUs we can surely come to a conclusion that we will be able to see better and faster GPUs in the near future.

×