PRACE training course "GPU Programming with CUDA"
(Course no. 1282018 in the training programme 2018 of Forschungszentrum Jülich)
Scientists who want to use GPU systems with CUDA
Some knowledge about Linux, e.g. make, command line editor, Linux shell, experience in C/C++
This course is given in English.
23-25 April 2018, 9:00-16:30
Jülich Supercomputing Centre, Ausbildungsraum 1, building 16.3, room 213a
Number of participants:
Dr. Jan Meinke, Jochen Kreutz, Dr. Andreas Herten, JSC;
Jiri Kraus, NVIDIA
Dr. Jan Meinke
Phone: +49 2461 61-2315
Please register until 31 March 2018 via theform at the PRACE web site
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 an NVIDIA GPU. The course will cover basic aspects of GPU architectures and programming. Focus is on the usage of the parallel programming language CUDA-C which allows maximum control of NVIDIA GPU hardware. 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 CUDA
- GPU libraries like CuBLAS and CuFFT
- Tools for debugging and profiling
- Performance optimizations
This course is a PRACE training course.