How GPU works?

graphics processing unit (GPU) is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device. GPUs are used in embedded systemsmobile phonespersonal computersworkstations, and game consoles.

A really comprehensive lecture from Pro. Mutlu:

GPUs and GPGPU Programming (pdf)

How to optimize for GPU / Graphics workload performance

This part includes key principles to be followed to avoid critical performance flaws when creating/optimization graphics apps. The following recommendations come from the experience of real industry and the developers within it.

  1. Understand the Target Device
    • You’ll need to learn as much info about the device as possible in order to understand different graphics architectures, to use the device in the most efficient manner possible.
  2. Profile the Workload
    • Identify the bottlenecks in the apps you are optimizing and determine whether there are opportunities for improvement.
  3. Perform Clear Well
    • Perform a clear on a framebuffer’s contents to avoid fetching the previous frame’s data on tile-based graphics architectures, which reduces memory bandwidth.
  4. Do Not Update Data Buffers Mid-Frame
    • Avoid touching any buffer when a frame is mid-flight to reduce stalls and temporary buffer stores.
  5. Use Texture Compression
    • Reduce the memory footprint and bandwidth cost of texture assets.
  6. Use Mipmapping
    • This increases texture cache efficiency, which reduces bandwidth and increases performance.
  7. Do Not Use Discard
    • Avoid forcing depth-test processing in the texture stage as this will decrease performance in the early depth rejection architectures.
  8. Do Not Force Unnecessary Synchronization
    • Avoid API functionality that could stall the graphics pipeline and do not access any hardware buffer directly.
  9. Move Calculations “To the Front”
    • Reduce the overall number of calculations by moving them earlier in the pipeline, where there are fewer instances to process.
  10. Group per Material
    • Grouping geometry and texture data can improve app performance.
  11. Do Not Use Depth Pre-pass
    • Depth pre-pass is redundant on deferred rendering architectures.
  12. Prefer Explicit APIs
    • Graphical app made using explicit APIs tend to run more efficiently, if set up correctly.
  13. Prefer Lower Data Precision
    • Lower precision shader variables should be used, where appropriate, to improve performance.
  14. Use All CPU Cores
    • Using multi-threading in apps is critical to efficient CPU use.
  15. Use Indexed Lists
    • Indexed lists can reduce mesh storage requirements by eliminating redundant vertices.
  16. Use On-chip Memory Efficiently for Deferred Rendering
    • Making better use of on-chip memory reduces overall system memory bandwidth usage.