Examples not working?

Work with RStudio #

R is available on Wynton HPC via a contributed environment module. It can be run interactively in the terminal via R on a development node, as explain on the how-to ‘Work with R’ page. To run R via the RStudio GUI, launch your personal RStudio Server as instructed below and access it via your local web browser. As explained, this requires running two separate SSH connections to the cluster: (i) one to launch RStudio Server, and (ii) one to connect to it.

Step 1. Launch your own RStudio Server instance #

Assuming you are already logged on to a development node, launch your personal RStudio Server instance as:

[alice@dev1 ~]$ module load CBI rstudio-server-controller
[alice@dev1 ~]$ rsc start
alice, your personal RStudio Server 2023.09.1-494 running R 4.3.2 is available on:

  <http://127.0.0.1:20612>

Importantly, if you are running from a remote machine without direct access
to dev1, you need to set up SSH port forwarding first, which you can do by
running:

  ssh -L 20612:dev1:20612 alice@log1.wynton.ucsf.edu

in a second terminal from your local computer.

Any R session started times out after being idle for 120 minutes.
WARNING: You now have 10 minutes, until 2023-11-15 17:06:50-08:00, to
connect and log in to the RStudio Server before everything times out.
Your one-time random password for RStudio Server is: y+IWo7rfl7Z7MRCPI3Z4

There are two things you should pay extra attention to here:

  1. The one-time random password that was generated

  2. The instructions how to log in to the cluster with SSH port forwarding

You will need both below.

Step 2. Connect to your personal RStudio Server instance #

On your local computer, log into the cluster in a second terminal following the instruction above. Make sure to use your own username and make sure to use the port number (e.g. 20612) that was assigned to you.

{local}$ ssh -L 20612:dev1.wynton.ucsf.edu:20612 alice@log1.wynton.ucsf.edu
alice1@log1.wynton.ucsf.edu:s password: XXXXXXXXXXXXXXXXXXX
[alice@log1 ~]$ 

Step 3. Open RStudio Server in your local web browser #

If you successfully completed the above two steps, and you made sure to use the correct port, then you should be able to open your personal RStudio Server in your local web browser by going to:

You will be presented with a ‘Sign in to RStudio’ web page where you need to enter:

  1. Your cluster username (e.g. alice)
  2. The one-time random password displayed in Step 1 (e.g. y+IWo7rfl7Z7MRCPI3Z4)

After clicking ‘Sign In’, you should be redirected to the RStudio interface.

To terminate the RStudio Server, start by exiting R by typing quit() at the R prompt. Then press Ctrl-C in the terminal where you called rsc start. Alternatively, run rsc stop in another terminal, e.g. the second one used in Step 2.

Troubleshooting #

Stuck at “R is taking longer to start than usual”? #

Some users report that they stuck when they try to log in to RStudio. After they enter their username and password, and click ‘Sign In’, they get to a page “R is taking longer to start than usual” with a spinner that never ends. The user is presented with three options ‘Reload’, ‘Safe Mode’, and ‘Terminate R’. Ideally, ‘Safe Mode’ or ‘Terminate R’ would solve the problem and let the user access the RStudio GUI. Unfortunately, for some users, none of these options help. Consecutive attempts to use rsc stop and rsc start fail for same reasons.

As of 2023-12-04, it is not clear why and when this happens. The one workaround we have found is to wipe the user’s RStudio sessions. For this, we recommend to use:

$ rsc reset --which=sessions

This will create a local copy of your problematic RStudio setup in file rstudio-config_<timestamp>.tar, and then, only then, remove the actually settings. The next time you call rsc start, you should start out with a fresh RStudio setup, and the login issue should be gone.

ERROR: Failed to check process PID 12345 on dev1.wynton.ucsf.edu over SSH #

If you get the following error when launching rsc start:

[alice@dev2 ~]$ rsc start
WARNING: Needs to SSH to dev1.wynton.ucsf.edu to check whether process 2132343
is still alive [/wynton/home/boblab/alice/.config/rsc/rserver.hostname:
21 bytes; 2024-09-28 15:56:13)]. If you don't have SSH key authentication set up,
you will be asked to enter your account password below. The current machine is
dev2.wynton.ucsf.edu
ERROR: Failed to check process PID 2132343 on dev1.wynton.ucsf.edu over SSH. 
Reason was: ssh: connect to host dev1.wynton.ucsf.edu port 22: No route to host

the reason is that rsc start tries to protect against launching more than one RStudio session at the same time on different machines. In order to confirm that you already running another RStudio session on another machine, it needs to access that machine via SSH, but if that fails you get the above error.

To troubleshoot this, start by making sure you can SSH to dev1.wynton.ucsf.edu. (1) If you can login manually, do that and call rsc stop there. This should resolve the above problem. (2) If you cannot access the machine, it could be that you have exhausted your CPU quota on that machine and it is very slow to respond. If you suspect this is the case, see ‘Running out of memory’ below. It could also be that the machine is not working or down, which is rare, but it happens. If it is down, it’s most likely already discussed on our Slack forum - please check there to confirm it is truly down. In the rare case that the machine is really down, try to call rsc reset and the retry with rsc start. If you still get the above error, retry with rsc reset --full.

Running out of memory #

If you get an ‘R Session Error’ dialog saying:

The previous R session was abnormally terminated due to an unexpected crash.

You may have lost workspace data as a result of this crash.

RStudio may not have restored the previously active project as a precaution. You may switch back to it using the Projects menu.

[OK]

one reason is that you ran out of memory and R was terminated by the operating system. Note that each user is limited to 96 GiB of RAM on the development node. Trying to use more than that, will cause the operating system to kill the underlying R process. When this happens, RStudio will likely keep running, but your R session was lost and reset.