Accelerating your applications with AMD GPUs
Online
This three-half-day program is aimed at scientists, researchers, application developers, and HPC practitioners who want to port, optimize, and profile their codes on AMD systems.
This training will equip participants with the skills to efficiently exploit AMD GPUs and CPUs for high-performance workloads.
Program highlights:
- Day 1: System Administration, ML/AI on AMD GPUs, AI Workflows, AI Programming assistant.
- Day 2: Python for GPU, HIP and ROCm introduction, OpenMP offloading, GPU-aware MPI.
- Day 3: Optimization and profiling, Pytorch optimization with LLMs, Neural Operators, AI Surrogates, Pytorch profiling.
- Each module includes hands-on exercises.
Audience: Researchers and engineers from academia or industry with prior HPC experience.
Prerequisites: Users are expected to login to the system before the training (just to check if access works). 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 (C, C++, Fortran, Python).
Date: December 2-4, 2025 (from 1pm to 5pm each day CET).
Registration: Mandatory till November 24, 2025.
Max capacity: 100
Format: Online. Zoom platform. A few days before the training, the meeting link will be sent to registered participants. Communication and users chat via a dedicated Slack channel.
Remote participants will access AMD infrastructures via the AMD Accelerator Cloud.
Language: English
Level: Intermediate
AMD experts:
Bob Robey is a Principal Member of Technical Staff in the Data Center GPU Software Solutions Group at AMD and is the global training Lead for GPU software. He has an extensive background in modeling compressible fluid dynamics with shock waves. He has led the Parallel Computing Summer Research Internship program at Los Alamos National Laboratory for seven years. He is also a co-author with Yuliana Zamora for book Parallel and High Performance Computing, Manning Publications. He has over thirty years of experience in parallel computing and a decade in GPU computing.
Giacomo Capodagilo is a Member of the Technical Staff at AMD, working on developing and delivering trainings on AMD GPU software. He has a PhD in Applied Mathematics from Texas Tech University and a Master’s in Energy Engineering from the University of Bologna (Italy). Prior to joining AMD, Giacomo was a Scientist at Los Alamos National Laboratory, working on numerical methods for the ocean and sea ice components of the Department of Energy’s climate model E3SM. Besides climate, Giacomo’s work includes urban flooding modeling, uncertainty quantification and probability density estimation, and numerical methods development for nonlocal problems.
Each participant will receive an AMD confirmed certificate.
Organized by AMD and NCC Poland (NCC Poland) within the EuroCC Project.
