Höchstleistungsrechenzentrum Stuttgart: AMD Instinct™ GPU Training

Prerequisites and content levels

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

Learn more about course curricula and content levels.

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 resources
- Developing Applications with the AMD ROCm
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 ROCm™ installation
- AMD Instinct™ MI200 GPU memory space overview
- Register pressure in AMD CDNA2™ 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
- Frontier user guide

Instructors

Bob Robey, AMD Global Training Lead for Data Center GPUs and additional AMD staff.

Learning outcomes

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.

Agenda (subject to change)

All times are CEST.

Day 1 - AMD Programming Model, OpenMP and MPI

12:45 - 13:00 Drop in to Zoom

13:00 HLRS Intro
13:10 AMD Presentation Roadmap and Introduction to the System for Exercises
13:20 Programming Model for MI200 and MI300 series
13:45 Programming Model Exercises
14:00 Break
14:10 OpenMP® Offloading with unified shared memory on the APU
14:55 Break
15:10 OpenMP® Exercises
15:40 OpenMP® Offloading on discrete GPUs
16:10 OpenMP® Exercises Part II
16:55 Wrap up

Day 2 - MPI and HIP and interoperability

12:45 - 13:00 Drop in to Zoom

13:00 HIP and ROCm
14:00 HIP Exercises
14:15 Break
14:30 Porting code to HIP
14:50 Porting Exercises
15:00 OpenMP® and HIP Interoperability
15:25 Interoperability Exercises
15:40 Break
15:55 Optimizing HIP Code
16:35 HIP Optimization Exercises
16:55 Wrapup

Day 3 - Performance Portable languages, C++ Std Par, MPI and Machine Learning

12:45 - 13:00 Drop in to Zoom

13:00 Performance Portability Frameworks; Intro to Kokkos
13:30 Kokkos Exercises
13:50 Break
14:00 GPU-Aware MPI on AMD GPUs
14:30 MPI Exercises
14:50 Break
15:00 C++ Standard Parallelism
15:30 C++ Standard Parallelism Exercises
15:50 Break
16:00 ML/AI on AMD GPUs
16:30 ML/AI Exercises
16:55 Wrapup

Day 4 - AMD Debuggers and Profiling Tools

12:45 - 13:00 Drop in to Zoom

13:00 Debugging with Rocgdb
13:40 Rocgdb Exercises
14:00 Break
14:15 GPU Profiling - Performance Timelines
14:55 Timeline Profiling Exercises
15:15 Break
15:30 Kernel Profiling with rocprof-compute
16:15 Kernel Profiling Exercises
16:45 Additional Training Resources
16:55 Wrapup

Please be aware that the talks and Q'n'A sessions will be recorded. You declare that you are aware of and consent to the recording by registering.

Registration has closed.

Late registrations after the registration phase are still possible according to the course capacity.

Fees

This course is free of charge.

Contact

Tobias Haas phone 0711 685 87223, training(at)hlrs.de

HLRS Training Collaborations in HPC and AI

HLRS is part of the Gauss Centre for Supercomputing (GCS), together with JSC in Jülich and LRZ in Garching near Munich. EuroCC@GCS is the German National Competence Centre (NCC) for High-Performance Computing. HLRS is also a member of the Baden-Württemberg initiative bwHPC. Since 2025, HLRS coordinates HammerHAI.

Further courses

See the training overview and the Supercomputing Academy pages.

AMD Instinct™ GPU Training

Veranstaltungsort

Prerequisites and content levels

Prerequisites

Content levels

Resources

Instructors

Learning outcomes

Agenda (subject to change)

All times are CEST.

Day 1 - AMD Programming Model, OpenMP and MPI

Day 2 - MPI and HIP and interoperability

Day 3 - Performance Portable languages, C++ Std Par, MPI and Machine Learning

Day 4 - AMD Debuggers and Profiling Tools

Fees

Contact

HLRS Training Collaborations in HPC and AI

Further courses

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Supercomputing Academy - Introduction to OpenMP

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Parallel Programming with MPI, OpenMP and Tools

Iterative Linear Solvers and Parallelization

Efficient Parallel Programming with GASPI