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R on HPC

Title: R on HPC – Introduction
Next Session: will be announced soon
Target Group: HPC Basics / HPC User
Language: English
Format: Online Tutorial

This tutorial focuses on accessing and running R on a High Performance Computing (HPC) system. Since the motivation to switch to an HPC system can be manifold, e.g. due to large memory requirements, GPU usage or increase of computation speed, this training will introduce R users to working in the HPC environment. We also provide an overview of selected Machine Learning methods and show how to work interactively or submit batch jobs. In the end, the participants will have the opportunity to do it all themselves in the Hands-On Session.

Agenda

  • Accessing R and RStudio on our HPC system
  • Overview of some of the main Machine Learning models (e.g. Linear and Logistic regression, Random Forest, etc.)
  • Introduction to model benchmarking in R
  • Introduction to parallelization in R: data-based and model-based
  • Hands-on Session: Exercises

Handouts

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

Prerequisites

Participants should have an understanding of Machine Learning methods and basic experience in using R. We recommend attending our Machine Learning on HPC – Introduction tutorial in advance or familiarize with Taurus and its compendium page.

Learning Outcomes

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.

funded by:
Gefördert vom Bundesministerium für Bildung und Forschung.
Gefördert vom Freistaat Sachsen.