• 🎓🔗 AMD Instinctâ„¢ GPU Training with HLRS
  • 2026-04-22T13:00:00+02:00
  • 2026-04-25T17:00:00+02:00
  • This course will give a deep dive into the AMD Instinctâ„¢ GPU architecture and its ROCmâ„¢ ecosystem, including the tools to develop or port HPC or AI applications to AMD GPUs.
When

Apr 22, 2026 01:00 PM to Apr 25, 2026 05:00 PM
(Europe/Berlin / UTC200)

Where

Online

Contact Name

Contact Phone

0711 685 87223

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Participants will be introduced to the programming models for the MI200 series GPUs and MI300A APU. The new unified memory programming model makes writing HPC applications much easier for a wide range of GPU programming models. We will cover how to use pragma-based languages such as OpenMP, the basic GPU programming language HIP, and performance portable languages such as Kokkos and RAJA. In addition, there will be presentations on other important topics such as GPU-aware MPI, and Affinity. The AMD tool suite, including the debugger, rocgdb, and the profiling tools rocprof, omnitrace, and omniperf will also be covered. A short introduction will be given into the AMD Machine Learning software stack including PyTorch and Tensorflow and how they have been used in HPC.

After this course, participants will

  • have learned about the many GPU programming languages for AMD GPUs
  • understand how to get performance scaling
  • have gained knowledge about the AMD programming tools
  • have gotten an introduction to the AMD Machine learning software
  • know about profiling and debugging.
Prerequisites

Some knowledge in GPU and/or HPC programming. Participants should have an application developer's general knowledge of computer hardware, operating systems, and at least one HPC programming language.

See also the suggested prereading below (resources and public videos).

Content levels

Basic: 1 hours
Intermediate: 7 hours
Advanced: 6 hours

Resources
  • Book on HIP programming - Porting CUDA
    • Accelerated Computing with HIP,  Yifan Sun, Trinayan Baruah, David R Kaeli,
      ISBN-13: ‎ 979-8218107444
  • Book on OpenMP GPU programming
    • Programming Your GPU with OpenMP, Tom Deakin and Tim Mattson,
      ISBN-13: ‎ 978-0262547536
  • Book of parallel and high performance computing topics
    • Parallel and High Performance Computing, Manning Publications, Robert Robey and Yuliana Zamora,
      ISBN-13: ‎ 978-0262547536
  • ENCCS resourses

  • AMD Lab Notes series on GPUOpen.com

    • Finite difference method - Laplacian part 1
    • Finite difference method - Laplacian part 2
    • Finite difference method - Laplacian part 3
    • Finite difference method - Laplacian part 4
    • AMD matrix cores
    • Introduction to profiling tools for AMD hardware
    • AMD ROCmâ„¢ installation
    • AMD Instinctâ„¢ MI200 GPU memory space overview 
    • Register pressure in AMD CDNA2â„¢ GPUs
    • GPU-Aware MPI with ROCm
    • Creating a PyTorch/TensorFlow Code Environment on AMD GPUs
    • Jacobi Solver with HIP and OpenMP offloading
    • Sparse matrix vector multiplication - part 1

  • Quick start guides at Oak Ridge National Laboratory

Registration information

Register via the button at the top of this page.
We encourage you to register to the waiting list if the course is full. Places might become available.

Fees

This course is free of charge.