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RStudio Server vs. RStudio Desktop OOD apps

Disclaimer: The differences presented here are applicable to RStudio in the FASRC Open OnDemand environment and not for the general RStudio Desktop vs. RStudio Server.

FASRC implemented two different Open OnDemand (OOD, also called VDI) applications for RStudio:

  • RStudio Server through the OOD app “RStudio Server”
  • RStudio Desktop through the OOD app “Remote Desktop” then launching RStudio Desktop

In this doc, we attempt to explain the major difference between the two.

RStudio Server

RStudio Server is our go-to RStudio app because it contains a wide range of precompiled R packages from bioconductor and rocker/tidyverse. This means that installing R packages in RStudio Server is pretty straightforward. Most times, it will be sufficient to simply:

> install.packages("package_name")

This simplicity was possible because RStudio Server runs inside a Singularity container, meaning that it does not use the host operating system (OS). For more information on Singularity, refer to our Singularity on the cluster docs.

Important notes:

  • User-installed R libraries will be installed in ~/R/ifxrstudio/\<IMAGE_TAG\>
  • This app contains many pre-compiled packages from bioconductor and rocker/tidyverse.
  • FAS RC environment modules (e.g. module load) and Slurm (e.g. sbatch) are not accessible from this app.
  • For the RStudio with environment module and Slurm support, go to our Open OnDemand page select Interactive Apps > Remote Desktop and refer to Open OnDemand Remote Desktop: How to open software

This app is useful for most applications, including multi-core jobs. However, it is not suitable for multi-node jobs. For multi-node jobs, the recommended app is RStudio Desktop.

RStudio Desktop

RStudio Desktop is a “bare” version of RStudio. Although it has some precompiled R packages, it is a much more limited list than the RStudio Server app.

RStudio Desktop runs on the host operating system (OS), the same environment as when you ssh to Cannon or FASSE.

This app is particularly useful to run multi-node applications because the you can specify the exact modules and packages that you need to load

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