GPU Programming Workshop @ LRZ 2025
OVERVIEW
In this 4-days online workshop you will learn how to accelerate your applications with OpenACC, CUDA C/C++ and CUDA Python on NVIDIA GPUs.
The workshop combines lectures about Fundamentals of Accelerated Computing with OpenACC, CUDA C/C++ and Python on a single GPU with a lecture about Accelerating CUDA C++ Applications with Multiple GPUs.
The lectures are interleaved with many hands-on sessions using Jupyter Notebooks. The exercises will be done on a fully configured GPU-accelerated workstation in the cloud.
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.
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
To get started, follow these steps:
- Create an NVIDIA Developer account at https://learn.nvidia.com/join Select "Log in with my NVIDIA Account" and then '"Create Account".
- 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.
- lf there are issues with WebSockets, try updating your browser.
We recommend Chrome or Firefox for an optimal performance. - Visit https://learn.nvidia.com/dli-event and enter the event code provided by the instructor.
- You're ready to get started. Please complete the survey at the end of the course to share your feedback.
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.
1st day Fundamentals of Accelerated Computing with OpenACC
Lecturer: Dr. Volker Weinberg (LRZ)
AGENDA (all times in CEST)
10:00-10:15 Welcome & Intro
10:15-12:00 Profiling
12:00-13:00 Lunch Break
13:00-15:00 OpenACC Directives and GPU Programming
15:00-15:30 Coffee Break
15:30-16:45 Data Management and Loop Otimizations
16:45-17:00 Q&A, Final Remarks
SLIDES
DOCUMENTATION
2nd day: Fundamentals of Accelerated Computing with CUDA C/C++
Lecturer: Dr. Momme Allalen (LRZ)
AGENDA (all times in CEST)
10:00-10:15 Introduction CUDA C/C++
10:15-12:00 Accelerating Applications with CUDA C/C++
12:00-13:00 Lunch Break
13:00-14:20 Managing Accelerated Application Memory with CUDA unified memory and nsys
14:20-14:30 Coffee Break
14:30-15:45 Asynchronous Streaming and Visual Profiling for Accelerated Applications with CUDA C/C++
15:45-16:00 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 CEST)
10:00-10:15
10:15-12:00
12:00-13:00 Lunch Break
13:00-15:00
15:00-15:30 Coffee Break
15:30-16:45
16:45-17:00 Q&A, Final Remarks
SLIDES
- tbd.
DOCUMENTATION
- bd.
4th day: Accelerating CUDA C++ Applications with Multiple GPUs
Lecturer: Dr. Momme Allalen (LRZ)
AGENDA (all times in CEST)
10:00-10:15 Welcome and Intro, Tools Overview
10:15-12:00 Introduction & Main Objectives
12:00-13:00 Lunch Break
13:00-14:20 Copy/Compute Overlap: Kernel Launches and Memory Copies in Non-Default Streams
14:20-14:30 Coffee Break
14:30-15:45 Multiple GPUs
15:45-16:00 Q&A, Final Remarks
SLIDES
DOCUMENTATION
Survey
- Please fill out the online survey under https://survey.lrz.de/index.php/571237?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.