This course will take place as an online event. The link to the online platform will be provided to the accepted registrants only.
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).
Prerequisites:
Some knowledge about Linux, e.g. make, command line editor, Linux shell (see for instance this overview), some experience in C
Language:
This course is given in English.
Date:
29 October-31 October 2024, 09:00-13:00
Further information:
please visit the JSC webpage at https://go.fzj.de/2024-gpu-openacc
Instructors:
Dr. Andreas Herten, Dr. Thorsten Hater, Dr. Kaveh Haghighi-Mood, Dr. Jan Meinke, JSC;
Jiri Kraus, Markus Hrywniak, NVIDIA