High-Performance Computing Center Stuttgart

Machine Learning with AMD GPUs and ROCm Software

January 11: This course is an additional instance of the same course provided on January 20, 2021.

Participants will be introduced to AMD's Instinct GPU portfolio and ROCm software ecosystem. The course will introduce the configuration of an AMD-based ML environment, along with the use of TensorFlow and PyTorch frameworks in conjunction with AMD GPUs. Exercises for participants will provide hands-on experience with the basics of using ROCm tools. The content will also include an introduction to performance profiling tools for AMD GPUs.

This course provides training in distributed Machine Learning.

Article about the course.

After this course, participants will

  •     have gained knowledge about configuration of ROCm software for AMD GPUs
  •     be able to install and use ROCm-accelerated builds of TensorFlow and PyTorch and apply on ResNet50
  •     be familiar with monitoring and profiling tools relevant to ML on AMD GPUs

Location

Online course
Organizer: HLRS, University of Stuttgart, Germany

Start date

Jan 21, 2021
13:30

End date

Jan 21, 2021
18:30

Language

English

Entry level

Basic

Course subject areas

Data in HPC / Deep Learning / Machine Learning

Topics

Big Data

Deep Learning

Machine Learning

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Prerequisites and content levels

Prerequisites:
  • Familiarity with Linux operating systems, including Linux shell (training will use Ubuntu)
  • Access to an SSH client to enable remote access for interactive portions of the training
  • Working proficiency in English (all training will be conducted in English)
  • Basic understanding of machine learning/deep learning concepts

Familiarity with TensorFlow and Pytorch will be a plus. Tutorial to explore prior to the course: "Learn and use ML" section: www.tensorflow.org/tutorials, a "Deep Learning with PyTorch" section: pytorch.org/tutorials, and a Python tutorial. In suggested prereading (videos and resources below) you will find more AMD material.

Please make sure to have a functioning working environment and remote access for interactive portions of the training prior to the course. In case of questions, please contact the course organizer (see below).

Content levels:
  • Intermediate: 1 hour
  • Advanced: 3 hours

Learn more about course curricula and content levels.

YouTube videos
Resources

Instructors

Derek Bouius (AMD), Will Wang (AMD), and Pak Lui (AMD)

Agenda

This course will be provided using Microsoft Teams. All times are CET.

13:30 - 14:00 Login and Microsoft Teams setup

14:00 - 14:15 Welcome - HLRS, AMD

14:15 - 14:45 Instinct and ROCm product overview

  • AMD Instinct GPUs
  • ROCm software overview
  • Software ecosystem supporting Instinct and ROCm
    • ML frameworks

14:45 - 15:30 ROCm basics

  • ROCm installation
  • Basic ROCm tools

15:30 - 15:35 Pause

15:35 - 16:35 Machine learning with AMD GPUs

  • Introduction to DL/ML on ROCm
  • TensorFlow installation and testing
  • PyTorch installation and testing
  • ML with multiple GPUs
  • ResNet50

16:35 - 16:45 Pause

16:45 - 17:45 Additional ROCm topics

  • Docker
  • HPC Job Scheduler and Monitoring
  • Math Libraries
  • Communication Libraries for Multi-GPU Scale-out

17:45 - 17:50 Pause

17:50 - 18:20 GPU performance profiling

18:20 - 18:30 Closing

Registration information

Registration is closed.

If the course is full, then please register to the waiting list, so that we can inform you when we can provide a second run of this course.

Fees

This course is free of charge.

PRACE PATC and bwHPC-C5

HLRS is part of the Gauss Centre for Supercomputing (GCS), which is one of the six PRACE Advanced Training Centres (PATCs) that started in Feb. 2012.
HLRS is also member of the Baden-Württemberg initiative bwHPC-C5.
This course is not part of the PATC curriculum and is not sponsored by the PATC program.

EXCELLERAT

This workshop is part of the collaboration between AMD and the Horizon-2020 Centre of Excellence EXCELLERAT. AMD is an EXCELLERAT Interest Group. See also the EXCELLERAT Service Portal for more information.

Contact

Rolf Rabenseifner phone 0711 685 65530, rabenseifner(at)hlrs.de
Khatuna Kakhiani phone 0711 685 65796, kakhiani(at)hlrs.de
Lorenzo Zanon phone 0711 685 63824, zanon(at)hlrs.de

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High-Performance Computing Center Stuttgart Nobelstraße 19, 70569 Stuttgart, Germany

Contact & Location

+49 711 685-87269 info(at)hlrs.de

A member of the Gauss Centre for Supercomputing, HLRS is one of three German national centers for high-performance computing.

www.gauss-centre.eu

HLRS is a central unit of the University of Stuttgart.

www.uni-stuttgart.de/en/

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