Considering porting or optimizing your code for AMD GPUs? This course will give an introduction to the AMD Instinct™ GPU architecture and its ROCm™ ecosystem, including the tools to develop or port HPC or AI applications to AMD GPUs. Participants will be introduced to the programming models for the MI200 and MI300 series GPUs and APUs. It has never been easier to program GPUs using 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. 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,
- have gained knowledge about the AMD programming tools,
- understand how to get performance scaling,
- have been introduced to the AMD machine learning (ML) and artificial intelligence (AI) software,
- know about profiling and debugging resources.
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.
Requirements:
Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on.
They are also required to abide by the ARCHER2 Code of Conduct.
Timetable:
13:00 - 17:00
Details to follow