tags |
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farm, rstudio |
[toc]
Titus Brown, [email protected]
June 19, 2023
To edit: / latest on github
Via ssh, as usual!
Allocate computational resources interactively via srun, and use a high priority queue.
For example, this:
srun -p high2 --time=0:30:00 --nodes=1 \
--cpus-per-task 2 --mem 5GB --pty /bin/bash
will allocate 5 GB of RAM for 30 minutes on the high2
partition/queue.
::::warning Note: the memory, CPUs, and time you allocate here will apply to your RStudio Server session! ::::
To use your own conda installation of R; if so, you'll need to have a pre-existing conda environment, or else you'll have to create one (see Appendix, below, for instructions). If you create one, you only need to do this once.
Activate the conda environment like so:
conda activate r_env
where r_env
is the name of your conda environent with r-base
installed.
::::info
There are several good reasons to use conda to install your own version of R. These reasons include:
- you can install many R packages directly from conda-forge without compiling them; e.g.
conda install r-tidyverse
to install tidyverse. - you can install your own packages from source as well, using e.g. devtools (
conda install r-devtools
) - you can pick from a wide variety of R versions! List them all with
conda list r-base
See the appendices to this document for instructions on installing conda and creating an R environment. ::::
If, instead of using conda, you want to use a system-installed R package, run:
module load R
You can select specific versions as listed by module avail R
.
::::warning If you have conda installed, you may need to run the following to use the system provided R module:
conda deactivate
unset CONDA_EXE
::::
module load rstudio-server
rstudio-launch
This will print out some specific instructions; you will need the ssh information as well as the RStudio Server password.
Note that this information will change every time you run rstudio-launch
: it is specific to your account and session!
::::warning
Note: rstudio-launch
is what is running RStudio Server! If it exits (because srun runs out of time, or you hit CTRL-C), your RStudio Server will stop as well!
::::
Create a new ssh connection into farm; on Mac OS and Linux computers, you can create a new terminal on your desktop/laptop computer and copy/paste from the instructions printed out by rstudio-launch
above.
For example, you will want to run something like:
ssh -L35181:cpu-3-51:35181 [email protected]
in a new window on your Mac OS X/Linux laptop/desktop
On Windows it's slightly trickier and depends on what software you are running.
Now, open the URL printed out by rstudio-launch
in a Web browser, and enter the provided username and password.
You should now be connected to RStudio Server! 🎉
At the end of your session, you can just close the tab and your ssh window(s).
If you want to be polite, you can more explicitly release the computational resources and shut things down by doing the following:
- use the File... menu in RStudio Server to close the session.
- type CTRL-C in the window where you ran
srun
andrstudio-launch
. - log out of your
srun
session by typingexit
. - log out of farm in both windows.
(You'll need to have conda installed before this; see below. If you have (base)
in your prompt, you're good to go!)
To create a conda environment named r_env
with R v4.3.0 installed, run:
conda create -n r_env -y r-base=4.3.0
There are several ways to install conda; we recommend using mambaforge.
Here are some commands you can copy/paste:
echo source ~/.bashrc >> ~/.bash_profile
curl -LO https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-Linux-x86_64.sh
bash Mambaforge-Linux-x86_64.sh
The last command will run a program that will ask a number of questions before installing conda; answer "yes" to all of them.
Then, log out and log back in.
Your shell prompt should now have (base)
at the beginning, indicating that conda was installed and you are in the base conda environment.
For documentation on using conda, see this tutorial.