2024-07-10 AI Training Series - High Performance Data Analytics Using R at LRZ (hdta5s24)
Online Course | AI Training Series - High Performance Data Analytics Using R at LRZ |
Number | hdta5s24 |
Available places | 86 |
Date | 10.07.2024 – 10.07.2024 |
Price | EUR 0.00 |
Location | ONLINE |
Room | |
Registration deadline | 05.07.2024 08:59 |
education@lrz.de |
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 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:
- 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 (incl. 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, crew) (A)
Prerequisites
- Basic knowledge of R
- AI Training Series: Orientation Session (or comparable previous knowledge)
- AI Training Series: Introduction to Container Technology & Application to AI at LRZ (or comparable previous knowledge)
- AI Training Series: Introduction to the LRZ AI Systems (or comparable previous knowledge)
Content Level
The content level of the course is broken down as:
Beginner's content: | 1,0h | 22% |
Intermediate content: | 2,0h | 45% |
Advanced content: | 1,5h | 33% |
Community-targeted content: | 0,0h | 0% |
Language
English
Lecturers
Dr. Johannes Albert-von der Gönna (LRZ)
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.
Withdrawal Policy
See Withdrawal
Legal Notices
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See Legal Notices
No. | Date | Time | Teacher | Location | Room | Description |
---|---|---|---|---|---|---|
1 | 10.07.2024 | 10:00 – 16:00 | Johannes Albert-von der Gönna | ONLINE | Lecture |