AI Training Series - High Performance Data Analytics Using R at LRZ

Course/Event Essentials

Event/Course Start
Event/Course End
Event/Course Format
Online
Live (synchronous)
Primary Event/Course URL
https://app1.edoobox.com/en/LRZ/Hybrid%…

Venue Information

Country: Germany
Venue Details: Click here

Training Content and Scope

Scientific Domain
Not scientific domain specific
Technical Domain
Artificial intelligence (AI), machine and deep learning
Programming Languages
Level of Instruction
Intermediate
Advanced
Sector of the Target Audience
Research and Academia
Language of Instruction
English

Other Information

Organiser
LRZ
Event/Course Description

ATTENTION: Due to illness of the lecturer the course has been postponed to 21.2.2024.

This course is part of the "LRZ AI Training Series", a series of courses aiming at the needs and expectations of data analytics, big data & AI users at LRZ. While focusing on these particular users and their use cases, this session as well as all other courses offered as part of the AI Training Series are, of course, open to all interested parties.

This course for academic participants from Germany will be organised as a hybrid event with the possibility to attend at LRZ in Garching near Munich or online.

Contents

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 application as frontend to the LRZ AI Systems. This is an easy to use and powerful, interactive platform for data analytics, machine learning and AI projects. Additionally, R can be used directly on the high performance computing (HPC) systems operated by LRZ, the Linux Cluster and SuperMUC-NG.

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

There will be three content blocks of roughly one and a half hour each (B=Beginner's, I=Intermediate, A=Advanced content):

  • The LRZ AI Systems and RStudio Server (B) / (I)
  • RStudio Server for AI projects (B) / (I)
  • R and the LRZ AI Systems: R package management and containerization (B) / (I)

 

  • R on the LRZ Linux Cluster: environment modules, R package management (B) / (I)
  • Slurm Workload Manager, interactive session, job processing (B) / (I)
  • Parallelization Using R: Overview and resources (I)
  • Pleasingly parallel workloads (B) / (I)

 

  • Introduction to worker queue scenario/weak coupling (rredis/doRedis, batchtools, clustermq) (I) / (A)
  • Shared memory parallelization (parallel/doParallel, foreach) (I) / (A)
  • Message passing (rmpi/doMPI) (I) / (A)
  • Futures/Promises (parallel, future, doFuture) (A)
  • Workflow management (targets) (A)