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POSTPONED -- PRACE training course "GPU Programming with CUDA"

This course was postponed to the second half of 2020.
(Course no. 872020 in the training programme 2020 of Forschungszentrum Jülich)

begin
04 May 2020 09:00
end
06 May 2020 16:30
venue
Jülich Supercomputing Centre, Ausbildungsraum 1, building 16.3, room 213a

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.


Contents levelin hoursin %
Beginner's contents:0 h0 %
Intermediate contents:9 h50 %
Advanced contents:9 h50 %
Community-targeted contents:0 h0 %

Prerequisites:

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

Target audience:

Scientists who want to use GPU systems with CUDA

Language:

This course is given in English.

Duration:

3 days

Date:

postponed to autumn 2020 (original 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:

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

Registration:

closed until the new date is set