GPU Programming Workshop @ LRZ October 2025

OVERVIEW

In this 4-days online workshop you will learn how to accelerate your applications with OpenACC, CUDA C++ and CUDA Python on NVIDIA GPUs.

The lectures are interleaved with many hands-on sessions using Jupyter Notebooks. The exercises will be done using a JupyterHub  to access the Alex system at NHR@FAU (Day 1) and a fully configured GPU-accelerated workstation in the cloud (Day 2 and Day 3).

The workshop is co-organised by Leibniz Supercomputing Centre (LRZ), Erlangen National High Performance Computing Center (NHR@FAU) and NVIDIA Deep Learning Institute (DLI). NVIDIA DLI offers hands-on training for developers, data scientists, and researchers looking to solve challenging problems with deep learning.

Day 1 (OpenACC) is offered outside of the NVIDIA DLI programme.

All instructors are NVIDIA certified University Ambassadors.

NVIDIA Deep Learning Institute

The NVIDIA Deep Learning Institute delivers hands-on training for developers, data scientists, and engineers. The program is designed to help you get started with training, optimizing, and deploying neural networks to solve real-world problems across diverse industries such as self-driving cars, healthcare, online services, and robotics.

TRAINING SETUP DAY 1

Exercises on Day 1 will be done on the Alex system at NHR@FAU using the JupyterHub.

  • Open https://hub.nhr.fau.de/jupyter-training-gpu-access.php
  • Enter the email you used to register for the course and click on "SUBMIT".
  • You will then get an e-mail with your personal access link to the Jupyterhub instance used during the course.
  • Click on the link in the e-mail to get access to the Jupyterhub.

To be able to visualise Nsight System profiler output during the course, please install Nsight System latest version on your local system before the course. The software can be downloaded from https://developer.nvidia.com/nsight-systems.

TRAINING SETUP DAY 2 & DAY 3

To get started, follow these steps:

  1. Create an NVIDIA Developer account at https://learn.nvidia.com/join Select "Log in with my NVIDIA Account" and then '"Create Account".
  2.  Make sure that WebSockets works for you:
    • Test your Laptop at http://websocketstest.com
    • Under ENVIRONMENT, confirm that '"WebSockets" is checked yes.
    • Under WEBSOCKETS (PORT 80]. confirm that "Data Receive", "Send", and "Echo Test" are checked yes.
  3. lf there are issues with WebSockets, try updating your browser.
    We recommend Chrome or Firefox for an optimal performance.
  4. Visit https://learn.nvidia.com/dli-event and enter the event code provided by the instructor.
  5. You're ready to get started. Please complete the survey at the end of the course to share your feedback.


1st day Fundamentals of Accelerated Computing with OpenACC

Lecturer: Dr. Volker Weinberg (LRZ)

AGENDA (all times in CET)

09:00-09:30  Welcome

09:30-11:00  Introduction and Profiling (incl. Coffee Break)

11:00-12:00 OpenACC Directives

12:00-13:00  Lunch Break

13:00-14:00  GPU Programming

14:00-15:15  Data Management (incl. Coffee Break)

15:15-15:45  Optimisations

15:45-16:00  Q&A, Final Remarks

SLIDES

LABS

DOCUMENTATION


2nd day: Fundamentals of Accelerated Computing with CUDA C/C++

Lecturer: Dr. Momme Allalen (LRZ)

AGENDA (all times in CET)

09:00-12:00  Fundamentals of Accelerated Computing with Modern CUDA C++

12:00-13:00  Lunch Break

13:00-15:00  Unlocking the GPU’s Full Potential: Asynchrony and CUDA Streams   

15:00-15:15  Coffee Break

15:15-16:45  Implementing New Algorithms with CUDA Kernels

16:45-17:00  Q&A, Final Remarks

SLIDES

DOCUMENTATION


3rd day: Fundamentals of Accelerated Computing with CUDA Python

Lecturer: Dr. Sebastian Kuckuk (NHR@FAU)

AGENDA (all times in CET)

09:00 - 12:00 Introduction to CUDA Python with Numba with coffee break

12:00 - 13:00 Lunch Break

13:00 - 14:30 Custom CUDA Kernels in Python with Numba

14:30 - 14:45 Coffee Break

14:45 - 16:00 Multidimensional Grids, and Shared Memory for CUDA Python with Numba


SLIDES

DOCUMENTATION


4th day: Q&A Session

Lecturers: Dr. Momme Allalen (LRZ), Dr. Sebastian Kuckuk (NHR@FAU), Dr. Volker Weinberg (LRZ)

AGENDA (all times in CET)

09:00-10:45 Q&A Session

10:45-11:00 Final Remarks (may end earlier)

SLIDES


Survey

  • Please fill out the online survey under https://survey.lrz.de/index.php/499587?lang=en
  • This helps us to
    • increase the quality of the courses,
    • design the future training programme at LRZ and GCS according to your needs and wishes,
    • get future funding for training events.


NEXT STEPS

Visit the NVIDIA Deep Learning lnstitute's website at https://www.nvidia.com/en-us/training/ to access more training and resources.

  • Start online, self-paced training in deep learning and accelerated computing (using the account you created today).
  • View upcoming workshops around the world and request an onsite workshop at your company or organization.
  • Learn about the University Ambassador Program.