PRACE training course "GPU Programming with CUDA"

begin

04 May 2020 09:00

end

06 May 2020 16:30

venue

Jülich Supercomputing Centre, Ausbildungsraum 1, building 16.3, room 213a

Target audience:

Scientists who want to use GPU systems with CUDA

Contents:

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.

Prerequisites:

Some knowledge about Linux, e.g. make, command line editor, Linux shell, experience in C/C++

Language:

This course is given in English.

Duration:

3 days

Date:

4-6 May 2020, 09:00-16:30

Venue:

Jülich Supercomputing Centre, Ausbildungsraum 1, building 16.3, room 213a

Number of participants:

maximum 25

Instructors:

Dr. Jan Meinke, Jochen Kreutz, Dr. Andreas Herten, JSC;
Jiri Kraus, NVIDIA

Contact:

Dr. Jan Meinke
Phone: +49 2461 61-2315
email: j.meinke@fz-juelich.de

Registration:

Please register until 31 March 2020 via the form at the PRACE web site (available in January 2020).