GPU Programming with CUDA (PRACE training course, online)
(Course no. 812021 in the training programme 2021 of Forschungszentrum Jülich)
This course is fully booked.
This course will take place as an online event. The link to the streaming platform will be provided to the registrants only.
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 level | in hours | in % |
|---|---|---|
Beginner's contents: | 0 h | 0 % |
Intermediate contents: | 9 h | 50 % |
Advanced contents: | 9 h | 50 % |
Community-targeted contents: | 0 h | 0 % |
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:
26-30 April 2021, 09:00-13:00
Venue:
online
Number of Participants:
maximum 30
Instructors:
Dr. Jan Meinke, Jochen Kreutz, Dr. Andreas Herten, JSC;
Jiri Kraus, Markus Hrywniak, NVIDIA
Contact:
Dr. Jan Meinke
Phone: +49 2461 61-2315
E-mail: j.meinke@fz-juelich.de
Registration:
This course is fully booked.