Using RStudio
Warning
Using RStudio differs between different HPC clusters.
We also recommend ThinLinc!
On UPPMAX
There is a system installed version, available via the “rstudio” command (you will get RStudio/1.1.423).
However, we recommend you to use a RStudio module.
Warning
We recommend ThinLinc because the graphics is more effective there!
Using ThinLinc
ThinLinc app:
<user>@rackham-gui.uppmax.uu.se
ThinLinc in web browser:
https://rackham-gui.uppmax.uu.se
This requires 2FA!Choose Xfce as the desktop environment (faster)
start a command line window
Using terminal
Remember to have X11 installed!
On Mac
install XQuartz
On Windows
Use MobaXterm or
Check for RStudio versions
Check all available versions with:
$ module avail RStudio
Output at UPPMAX as of March 10 2024
[bjornc@rackham5 ~]$ ml av RStudio ------------------------------------- /sw/mf/rackham/applications ------------------------------------- RStudio/1.0.136 RStudio/1.1.423 RStudio/2022.02.0-443 RStudio/2023.06.0-421 RStudio/1.0.143 RStudio/1.1.463 RStudio/2022.02.3-492 RStudio/2023.06.2-561 RStudio/1.0.153 RStudio/1.4.1106 RStudio/2022.07.1-554 RStudio/2023.12.1-402 (D) Where: D: Default Module Use "module spider" to find all possible modules and extensions. Use "module keyword key1 key2 ..." to search for all possible modules matching any of the "keys".
load R_packages
module load RStudio
run
rstudio &
from the command line, and waitit might take 5-10 minutes for RStudio to start, especially if you loaded R_packages as well, but once it starts, there should be no further delays
do not start RStudio through the graphical menu system in ThinLinc, this will not have access to loaded modules.
if it takes a long time and might be due to that you have saved a lot of workspace
Example:
Demo
$ module load R/4.1.1
$ module load RStudio/2023.12.1-402
$ rstudio &
If you’re going to run heavier computations within RStudio then you have to remember that you need to do it inside an interactive session on one of the computation nodes, and not on a login node. But if you mostly want to use it as a pretty code editor then you can run it on the login node as well.
To use Rstudio on a compute node, start by asking SLURM for an interactive allocation (within the ThinLink session). E.g.
$ interactive -A naiss2023-22-44 -p devcore -n 4 -t 10:00
On Bianca
When logging onto Bianca, you are placed on a login node, which nowadays has 2 CPU and a few GB of RAM. This is sufficient for doing some light-weight calculations, but interactive sessions and batch jobs provide access to much more resources and should be requested via the SLURM system.
The desktop client version of ThinLinc does not work for Bianca. Instead you run and login to ThinLinc in the browser:
On HPC2N
Rstudio also exists on Kebnekaise but is only installed on the ThinLinc login nodes and not on the compute nodes (and also not on the regular login nodes accessible with SSH). Thus, Rstudio should only be used for development and very light analysis, since there is no way to submit a job to the compute nodes.
Login to ThinLinc desktop application by providing the following
server: kebnekaise-tl.hpc2n.umu.se
username
password
Alternatively, you can use ThinLinc in the browser: https://kebnekaise-tl.hpc2n.umu.se:300/
When in ThinLinc, you can start Rstudio either from the menu (version 4.0.4) or from the command line. If you start it from the command line you first need to load R and its prerequisites, but you can pick between several versions this way.