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
ENCCS resourses
- Developing Applications with the AMD ROCm
LAB-NOTE series on GPUOpen.com
- Finite difference method - Laplacian part 1
- Finite difference method - Laplacian part 2
- AMD matrix cores
- Introduction to profiling tools for AMD hardware
- AMD ROCm™ installation
- AMD Instinct™ MI200 GPU memory space overview
Quick start guides at Oak Ridge National Laboratory
- Crusher quick-start guide
- Frontier user guide

Instructors

Bob Robey, Essam Morsi, George Markomanolis (AMD)

Agenda (subject to change)

All times are CEST.

Day 1

12:45 - 13:00 Drop in to Zoom

13:00 HLRS Intro
13:15 AMD Presentation Roadmap
13:25 Introduction to the System for Exercises
13:50 Introduction to the AMD Architecture, including FPGA
14:10 Overview of ROCm and Compilers, Infinity
Hub/HPC Community
14:30 Break
14:40 Introduction to HIP
15:40 HIP Exercises
16:00 Break
16:15 Porting applications to HIP
16:40 Porting exercises
16:55 Wrapup

Day 2 - Additional GPU Programming Languages

12:45 - 13:00 Drop in to Zoom

13:00 Introduction to OpenMP®
13:50 OpenMP® Exercises
14:30 Break
15:00 Advanced OpenMP® and Mixing HIP and OpenMP®
16:00 Break
16:10 Performance Portability Frameworks; Intro to Kokkos
16:40 Kokkos Exercises
16:55 Wrapup

Day 3 - AMD Performance Considerations and Debugging

12:45 - 13:00 Drop in to Zoom

13:00 AMD Communication Fabrics and GPU-Aware MPI
13:30 GPU-Aware Exercises
13:45 Break
13:55 AMD Node Memory Model
14:35 Memory Model Exercises
14:50 Break
15:00 Affinity - Placement, Ordering and Binding
15:40 Affinity Exercises
16:00 Debuggers - rocgdb
16:40 Rocgdb exercises
16:55 Wrapup

Day 4 - AMD Profilers and Machine Learning

12:45 - 13:00 Drop in to Zoom

13:00 Introduction to rocprof
13:20 Rocprof Exercises
13:30 Introduction to Omnitrace
14:00 Omnitrace Exercises
14:15 Introduction to Omniperf
14:40 Omniperf Exercises
14:50 Break
15:00 Machine Learning in HPC; Introduction to ML on AMD
15:30 Examples of Machine Learning projects
16:55 Wrapup

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.

Registration will end on September 8, 2023 at 11:59 PM.

Fees

This course is free of charge.

Contact

Khatuna Kakhiani phone 0711 685 65796, kakhiani(at)hlrs.de
Lorenzo Zanon phone 0711 685 63824, zanon(at)hlrs.de

HLRS Training Collaborations in HPC

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.

Further courses

See the training overview and the Supercomputing Academy pages.