2021-04-06 Data Analytics, Big Data & AI Training Week (hdta1s21)

Contents

This course series on Data Analytics, Big Data & AI Training offers the following course modules which build up on each other and can be selected individually during registration depending on the knowledge of the participants.

Module:Introduction to GNU/Linux and SSH - Q&A

Date: 06.04.2021, 09:00-12:30 CEST
Lecturer: Dr. Martin Ohlerich (LRZ)

This course module provides an introduction to GNU/Linux, the Unix shell and how to work on remote systems using Secure Shell (SSH). GNU/Linux is a family of open source operating systems, powering all different kinds of hardware: wearable and mobile devices, desktop and notebook computers, the majority of web servers and cloud instances as well as most high performance computing clusters and supercomputes. The typical command line interface is a Unix-like shell. It serves as interactive command and scripting language, allowing users to control the system and to automate tasks of varying complexity. SSH is a cryptographic network protocol which is typically used to login and execute commands on remote (GNU/Linux) systems.

The course module opens with a short historical overview of GNU/Linux and some common concepts and terminology will be explained. Then the focus is directed toward working with the Unix shell on a remote system by guiding participants to install and configure a SSH client on their local systems. Different applications for remote access and file transfer will be introduced. Shell commands will then be used to navigate the file system and directories of a remote system, then the mechanisms of file manipulation and ownership will be explored. This is followed by the presentation of additional useful commands and concepts, as well as a discussion of the characteristics of the shell environment. A conceptual and practical introduction to SSH keys will also be given.

This will be an interactive Q&A session. Registered participants will receive preparatory tutorial material in advance of the training event.They are expected to work with these self-study materials prior to the actual session, which will then primarily be used to answer any remaining questions.

Participants will gain essential knowledge and skills necessary to successfully interact with the command line interface of a GNU/Linux system, a basic requirement when using the LRZ supercomputing and cloud infrastructure for their own projects.

Prerequisites:

None

Module: Introduction to the LRZ HPC Infrastructure

Date: 06.04.2021, 13:30-17:00 CEST
Lecturer: Dr. Johannes Albert-von der Gönna (LRZ)

In this introductory course module we will give an overview of the High Performance Computing (HPC) systems operated by the Leibniz Supercomputing Centre (LRZ).

First, a general introduction to HPC systems as well as a brief discussion of historical developments and current trends will be given. Then, the different systems at LRZ will be presented in detail. While touching upon the world leading supercomputer SuperMUC-NG, the focus will be directed at different cluster and storage systems as part of the LRZ Linux Cluster. These systems will be further explored in a dedicated hands-on session. This will prepare participants to succesfully run compute jobs on LRZ HPC systems and will cover important system components like the environment module system and the Slurm Workload Manager. Additonal supporting software services will also be presented.

The material will be presented as a combination of lectures, demos and hands-on sessions, with a focus on the latter. There will be breaks during the session.

Participants will gain the general understanding and skills necessary to efficiently utilize the LRZ supercomputing infrastructure for their own projects.

Prerequisites:

• Module: Introduction to GNU/Linux and SSH (or comparable previous knowledge)

Module: Introduction to the LRZ Compute Cloud

Date: 07.04.2021, 09:00-12:30 CEST
Lecturer: PD Dr. Juan Durillo Barrionuevo (LRZ)

The aim of this course module is to provide participants with the knowledge and skills necessary to efficiently utilise the LRZ Compute Cloud infrastructure for their own projects. The course module consists of mini lectures, demos and hands on sessions (breaks included) covering the following topics:

• Fundamentals of cloud computing and Infrastructure as a Service (IaaS) clouds

• Overview of the hardware of the LRZ Compute Cloud

• Using the LRZ Compute Cloud via the web Interface

• Using the LRZ Compute Cloud via the command line

Prerequisites:

• Module: Introduction to GNU/Linux and SSH (or comparable previous knowledge)

Module: Using R at LRZ

Date: 07.04.2021, 13:30-17:00 CEST
Lecturer: Dr. Johannes Albert-von der Gönna (LRZ)

R is a highly popular and powerful programming language for data analysis and graphics, used in many research domains. The Leibniz Supercomputing Centre (LRZ) is addressing the needs of R users by facilitating various ways of working with R on LRZ systems.

For one it is hosting a RStudio Server web service that provides an easy to use and powerful platform mostly targeted at interactive analyses. This service can, however, also be used as a gateway to the high performance computing (HPC) systems at LRZ. Additionally, R can be employed directly on the massively parallel Linux Cluster and SuperMUC-NG as well as on specialized and GPU-enhanced machine learning (ML) systems.

In this course module, the different possibilities of using R  at LRZ for data analytics and machine learning projects will be demonstrated and excercised in hands-on session. Guidelines and best practice examples for running R applications efficiently on the various systems will be provided. Special attention will be paid to different ways of parallelizing R code in order to utilize LRZ's HPC infrastructure. There will be breaks during the session.

Prerequisites:

• Module: Introduction to GNU/Linux and SSH (or comparable previous knowledge)
• Module: Introduction to the LRZ HPC Infrastructure (or comparable previous knowledge)
• Basic knowledge of R

Module: Introduction to Container Technology & Application to AI at LRZ

Date: 08.04.2021, 13:30-17:00 CEST
Lecturer: Florent Dufour (LRZ)

Since the introduction of docker back in 2013, container technology has become the industry standard for software packaging, distribution, and deployment.

Creating a container consists in bundling an application, its runtime, dependencies, libraries, settings etc. in one single unit that can later run independently of the underlying infrastructure. Unlike virtual machines, containers are lightweight and yield higher performances while providing greater versatility and interoperability. As containers accommodate an easy, safe, reliable, and scalable way to run applications and pipelines, they are an attractive candidate for high performance computing and artificial intelligence workloads.

With this module, we will showcase the most enticing features and niceties offered by containers. Not only will we explore their history and implementations, but we will also dive into actual and cutting edge uses with a particular emphasis on artificial intelligence tasks, reproducible biomedical pipelines, and automated workflows.

Participants will roll up their sleeves and get their hands on the compute cloud of LRZ to set containers in action. By the end of the course module, participants will be able to transfer their experience and knowledge to their specific use-cases and requirements.

Prerequisites:

• Module: Introduction to GNU/Linux and SSH (or comparable previous knowledge)

Module: Introduction to the LRZ AI Infrastructure

Date: 08.04.2021, 13:30-17:00 CEST
Lecturer: PD Dr. Juan Durillo Barrionuevo (LRZ)

The aim of this course module is to give an overview of the LRZ AI Infrastructure,  provide participants with the knowledge and skills necessary to efficiently utilise them. The course module consists of mini lectures, demos and hands on sessions (breaks included) covering the following topics:

• Resources overview of the LRZ AI Infrastructure

• Fundamentals of ML training

• Distributed ML training

Prerequisites:

• Module: Introduction to GNU/Linux and SSH (or comparable previous knowledge)
• Module: Introduction to the LRZ HPC Infrastructure (or comparable previous knowledge)
• Module: Introduction to Container Technology & Application to AI at LRZ
  

Intel® AI HPC Workshop #1: Machine Learning Module

Date: 09.04.2021, 09:00-12:30 CEST
Lecturers: Severine Habert (Intel), Shailen Sobhee (Intel) and others

The use of data analytics techniques, such as Machine Learning and Deep Learning, has become the key for gaining insight into the incredible amount of data generated by scientific investigations (simulations and observations). It is crucial for the scientific community to incorporate these new tools in their workflows to take advantage of these increasingly large and complex datasets.

This session will cover the following topics:

• Introduction and Hardware Acceleration for AI
• OneAPI Toolkits Overview, Intel® AI Analytics toolkit and oneContainer
• Deep dive in Machine Learning tools

Intel® AI HPC Workshop #2: Deep Learning Module

Date: 09.04.2021, 13:30-17:00 CEST
Lecturers: Severine Habert (Intel), Shailen Sobhee (Intel) and others

The demand of using Deep Learning techniques in many scientific domains is rapidly emerging and the requirements for large compute and memory resources is increasing. One of the consequences is the need of the high-performance computing capability for processing and inferring the valuable information inherent in the data. Based on Intel^® technology, the high-end system operated at the Leibniz Supercomputing Centre (LRZ), SuperMUC-NG, targets among others also workloads at the crossroads of AI and HPC.

This session will cover the following topics:

• Deep dive in Deep Learning tools
  • OneDNN
  • Intel® Optimized Tensorflow
  • Intel® Optimized PyTorch and Intel® Optimization for PyTorch
  • Intel® Low Precision Optimization Tool
  • OpenVINO
• Distributed training and Federated Learning
  
  • Distributed Machine Learning
  • Distributed Deep Learning training
  • Federated Learning

Hands-On

Will be utilizing the LRZ Linux Cluster, Compute Cloud and AI Systems.

Language

English

Lecturers

Dr. Johannes Albert-von der Gönna (LRZ), Florent Dufour (LRZ),  PD Dr. Juan Durillo Barrionuevo (LRZ), Dr. Martin Ohlerich (LRZ), Severine Habert (Intel), Shailen Sobhee (Intel) and others

Prices and Eligibility

The course is open and free of charge for academic participants from Germany.

Registration

Please register with your official e-mail address to prove your affiliation.You can select the course modules you wish to attend during registration.

Withdrawal Policy

See Withdrawal

Legal Notices

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See Legal Notices.