The lecture “computer graphics” gives an introduction to modern computer graphics and GPU-based computation.

Its intended audience are students of computer science, and more generally any person with a solid background in programming and mathematics interested in the topic.

The lecture is hosted by the Alan Turing Institute for Data Science and supported by Nvidia.

Scientific topics covered in the lecture are as follows.

• Mathematical and algorithmic foundations:
  • affine and projective coordinates, linear transformations
  • affine and projective geometry, shapes, splines, clipping
  • -pixels discretization, rasterization, resolution
  • colour schemes, colour spectrum
• Rendering:
  • the rendering pipeline
  • openGL, Direct3D APIs
  • Texturing: texture, light/shadow and bump mappings
  • Occlusion, buffering, culling
  • Lighting and shading, ray tracing, radiosity
  • Reflection, refraction, diffraction
• GPU computing:
  • GPU architecture
  • GPU computing APIs, CUDA
  • CPU vs GPU parallelisation, toolbox APIs
  • Data science and machine learning on GPU, incl. “deep learning”