GPU Programming with CUDA (PRACE training course, online)
(Course no. 1582022 in the training programme 2022 of Forschungszentrum Jülich)
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/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
- Advanced GPU programming model
- CUDA Fortran in a nutshell
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:
25-29 April 2022, 09:00-13:00
Venue:
online
Number of Participants:
maximum 30
Instructors:
Dr. Jan Meinke, Jochen Kreutz, Dr. Andreas Herten, Dr. Kaveh Haghighi-Mood, JSC;
Jiri Kraus, Markus Hrywniak, NVIDIA
Contact:
- Institute for Advanced Simulation (IAS)
- Jülich Supercomputing Centre (JSC)
Room 4012
Application:
Please register until 9 April 2022 via the form at the PRACE web site.
Applicants will be notified, whether they are accepted for participitation.