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GPU Computing

CITHN4015Elective Modules6 ECTSEnglishUnregelmäßigStudiengangsbündel Heilbronn
AI-edited module sheet. Based on the TUMonline module description, edited for readability.Original in TUMonline

What it is about

You learn the basics of parallel programming on GPUs, the structure and use of GPU hardware, as well as programming models and optimization techniques. In the end you will be able to write GPU kernels in CUDA/HIP/SYCL, integrate them into C/C++ programs, debug and profile programs, and design and implement simple GPU applications.

What you will be able to do

  • Understand GPU architectures
  • Write GPU kernels in CUDA/HIP/SYCL and launch them from C/C++
  • Understand GPU execution hierarchy
  • Know GPU memory hierarchy (shared, global, registers)
  • Map algorithms to GPU models and choose strategies
  • Debug and profile GPU programs
  • Assess, analyze and improve performance
  • Design and implement small GPU applications

What the module consists of

  • VorlesungPresentation of concepts for GPU architecture and programming
  • Hands-On-ÜbungenPractical application of concepts through programming tasks
  • Hausaufgaben / kleine ProjekteCentral learning component: independent implementation of programming tasks and presentation of solutions

Teaching method

  • PräsentationDelivery of theoretical foundations
  • Hands-On / projektbasiertes LernenDeepening through practical exercises and independent projects for application in real contexts
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Official page in TUMonline · Details are not binding.