Oct 24, 2023 to Oct 27, 2023
(Europe/Berlin / UTC200)



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GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GPUs offers high application performance by offloading compute-intensive portions of the code to the GPU. The course will cover basic aspects of GPU architectures and programming. Focus is on the usage of the directive-based OpenACC programming model which allows for portable application development. Examples of increasing complexity will be used to demonstrate optimization and tuning of scientific applications.

Topics covered will include:

  • Introduction to GPU/Parallel computing
  • Programming model OpenACC
  • Interoperability of OpenACC with GPU libraries (like cuBLAS and cuFFT) and CUDA
  • Multi-GPU Programming with MPI and OpenACC
  • Tools for debugging and profiling
  • Performance optimization

The course consists of lectures and interactive hands-on sessions in C or Fortran (the attendee’s choice).


Some knowledge about Linux, e.g. make, command line editor, Linux shell (see for instance this overview), some experience in C

Target audience:

Scientists who want to use GPU systems with OpenACC


This course is given in English.


Registration here.