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PRACE training course "GPU Programming with CUDA"

(Course no. 1102019 in the training programme 2019 of Forschungszentrum Jülich)

begin
01 Apr 2019 09:00
end
03 Apr 2019 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:
1-3 April 2019, 9:00-16:30
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:
Please register until 28 February 2019 via the form at the PRACE web site



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