R on HPC – Introduction

In this tutorial, we will introduce R users to the advantages of working on R on a High Performance Computing cluster. We will provide an overview of the most common Machine Learning methods and then look into how exactly we can explore their parallelization for the purposes of speeding up the run time. We will also show how some of the benchmarking packages in R work. In the end, the participants will have the opportunity to do it all themselves in the Hands-on Session.

Course Details

Title: R on HPC – Introduction
Last Session: 11.07.2022, 10 a.m. – 3 p.m. (Speakers: Neringa Jurenaite, Dr. Iryna Okhrin, Dr. Taras Lazariv)
Registration: https://event.zih.tu-dresden.de/nhr/r-hpc
Target Group: HPC Basics / HPC User
Language: English
Format: Tutorial

Agenda

Handouts

The course material (slides, sample application) will be available.

Pre-Knowledge

Participants should have an understanding of Machine Learning methods and basic experience in using R. We recommend attending ML-HPC-B NHR Tutorial in advance or familiarize with Taurus and its compendium page.

Post-Knowledge

Participants will understand the application of main Machine Learning methods in R and be aware of corresponding issues. Further, they will know more about the implementation of parallelization and benchmarking of Machine Learning models in R on an HPC cluster using specific examples.

Contact

Check out the other trainings by ScaDS.AI Dresden/Leipzig.

TU
Universität
Max
Leibnitz-Institut
Helmholtz
Hemholtz
Institut
Fraunhofer-Institut
Fraunhofer-Institut
Max-Planck-Institut
Institute
Max-Plank-Institut