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GPU Programming with CUDA (PRACE training course, online)

Exact date to be determined.

This course will take place as an online event. The link to the streaming platform will be provided to the registrants only.

 

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01 Apr 2021 09:00
end
01 Apr 2021 13:00
venue
Online

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:

5 half days

Date:

probably April/May 2021

Venue:

online

Number of Participants:

maximum 30

Instructors:

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

Contact:

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

Registration:

Please register until 15 March 2021 via the form at the PRACE web site (will be available in January).