🎓 GPU Programming using CUDA

The course provides an introduction to the programming language CUDA which is used to write fast numeric algorithms for NVIDIA GPUs. Focus is on the basic usage of the language, the exploitation of the most important features of the GPU (massive parallel computation, shared memory) and efficient usage of the hardware to maximize performance. An overview of the available development tools and some advanced features of the language is given.

The course is split in two parts in two subsequent weeks: 

Part 1 starts with an introduction to CUDA, covers the most basic topics necessary and ends with comments on usage of CUDA with more modern C++.
Part 2 introduces more features of GPUs and how to use them with CUDA. Further correctness checking and kernel level profiling will be covered as well as some more advanced topics.

You may attend only part 2 if you have already a good basic knowledge of CUDA (see topics of part 1 in the agenda).

Course subject areas

Hardware Accelerators

Parallel Programming

Topics

GPU Programming

Prerequisites and content levels

For part 1 (introductory)

Programming experience in any of C, C++, or Fortran. Exercises will use a Linux cluster. Therefore you should have some basic knowlegde about how to work with a Linux shell and a text editor in a shell. Resources for this could be e.g. https://ubuntu.com/tutorials/command-line-for-beginners and for an editor https://opensource.com/article/19/3/getting-started-vim. Some knowledge about parallel programming is a plus.

For part 2 (advanced)

Additionally to the prerequisites above you should be familiar with the topics of part 1.

Content levels

• Basic: 12 hours
• Intermediate: 6 hours
• Advanced: 3 hours

Learn more about course curricula and content levels.

Instructors

Tobias Haas (HLRS)

Learning outcomes

After this course, participants will:

• be familiar with the CUDA programming model,
• have basic knowledge on performance optimization and profiling of CUDA code,
• be aware of available correctness checking tools,
• have seen a first approach to multi-GPU programming,
• have an overview of important CUDA libraries.

Agenda (preliminary)

All times are local times in the central European time zone (Berlin).

Drop in to the video conference (8:45 - 9:00)

Course will take place from 9:00 - 12:30 on each day.

Cluster dry run on Mon Jan 19

Part 1 (Tue - Thu, Jan 20 - 22)

Day 1

• Basics about CUDA
• Kernel, kernel launch, host/device functions
• Memory management: host and managed memory
• Synchronization
• Error handling

Day 2

• Profiling and NVTX annotations
• Memory management: pinned and device, unified memory
• Overview of CUDA libraries

Day 3

• GPU architecture
• Performance optimization: memory access patterns and cache
• Coalesced memory access
• Modern C++ and GPUs

Part 2 (Mon - Thu, Jan 26 - 29)

Day 4

• Shared and constant memory
• Bank conflics
• Atomic operations

Day 5

• CUDA streams
• Introduction to Multi-GPU

Day 6

• wrapShuffle, CUB
• cooperative_groups

Day 7

• Kernel-level profiling and correctness checking
• Other programming methods (using base language constructs, pragmas and libraries)
• Interoperability with OpenMP

Handouts

Each participant will get access to all slides (PDF).

Exercises

Although this is an online course, the exercises will be very interactive using break out rooms. Participants will work on HLRS's systems.

Registration information

Apply for this course via the button at the top of this page.

Registration closes on January 7, 2026.

Fees

• Employees of the HLRS or the Jülich Supercomputing Centre (JSC) or the Leibniz Supercomputing Centre (LRZ): 0 Euro
• Students without master’s degree or equivalent: 32.50 Euro
• PhD students or employees at a German university or public research institute: 67.50 Euro
• PhD students or employees at a university or public research institute in an EU, EU-associated or PRACE country other than Germany: 135 Euro
• PhD students or employees at a university or public research institute outside of EU, EU-associated or PRACE countries: 270 Euro
• Other participants, e.g., from industry, other public service providers, or government: 690 Euro

Our course fee includes coffee breaks (in classroom courses only).

For lists of EU and EU-associated coutries, and PRACE countries have a look at the Horizon Europe and PRACE website.