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FAQ

Over time, we have discovered a few problems that many users experience. The solutions to these common problems are posted here.

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Connection Questions

Why does MobaXTerm throw Authorisation not recognized error when I try to log into Palmetto?

This error looks like this:

/usr/bin/xauth:  error in locking authority file /home/username/.Xauthority
MoTTY X11 proxy: Authorisation not recognized

Usually this happens when your home directory is full. Log into Palmetto with another terminal application (for example, PuTTY) and free up some space in your home directory. Then, MobaXTerm should work fine.

Why do I see the notice REMOTE HOST IDENTIFICATION HAS CHANGED when connecting to Palmetto?

If you are a Mac user, and try to ssh into Palmetto from the terminal, you might get this error message:

@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
@ WARNING: REMOTE HOST IDENTIFICATION HAS CHANGED! @
@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
IT IS POSSIBLE THAT SOMEONE IS DOING SOMETHING NASTY!
Someone could be eavesdropping on you right now (man-in-the-middle attack)!
It is also possible that a host key has just been changed.
The fingerprint for the RSA key sent by the remote host is
SHA256:Z2WLGvz7vX2t9VPap6ITwS3cBlCafN69FoIm8wmmF6g.
Please contact your system administrator.
Add correct host key in /Users/abcd/.ssh/known_hosts to get rid of this message.
Offending RSA key in /Users/abcd/.ssh/known_hosts:5
RSA host key for login.palmetto.clemson.edu has changed and you have requested strict checking.
Host key verification failed.

This is a common problem, and it's easy to fix. Please find the line "Offending RSA key" in the error message. In the example above, the number of the offending key is 5. This means that we have to remove 5th line from the lists of known SSH hosts so this line could be recreated.

There are several ways to fix the error. The first one is, to type in terminal

sed -i '5d' ~/.ssh/known_hosts

(Please replace the number 5 with the number of the offending RSA key from the error message)

Alternatively, you can type in terminal

perl -pi -e 's/\Q$_// if ($. == 5);' ~/.ssh/known_hosts

(Again, instead of number 5, put the number of the offending RSA key)

Compute Questions

How do I perform a fine-grained check for resource availability?

The following answer applies to Palmetto 1 and the PBS job scheduler. For Palmetto 2, see our main documentation.

Up until recently, whatsfree has been the standard tool to identify available computing resources on Palmetto. However, with the additional of compute nodes with large number of cores, large amount of memory, and multiple GPUs card, we have seen instances of nodes using only a portion of the available cores/memory/GPU but are still regarded as unavailable with whatsfree.

To address this issue and improve utilization on Palmetto, a new tool called freeres (abbreviation of free resources) has been made available. This tool provides a more fine-grained view into individual nodes of a specific phase. For example, at 15:12 November 19, 2021, whastfree shows that there are no available nodes on phases 18b, 18c, and 19a:

[lngo@login001 ~]$ whatsfree

C2 CLUSTER (newest nodes with interconnect=HDR except for phase19b)
PHASE 18b TOTAL = 65 FREE = 0 OFFLINE = 0 TYPE = Dell R740 Intel Xeon 6148G, 40 cores, 372GB, HDR, 25ge, V100
PHASE 18c TOTAL = 10 FREE = 0 OFFLINE = 0 TYPE = Dell R740 Intel Xeon 6148G, 40 cores, 748GB, HDR, 25ge, V100
PHASE 19a TOTAL = 28 FREE = 0 OFFLINE = 0 TYPE = Dell R740 Intel Xeon 6248G, 40 cores, 372GB, HDR, 25ge, V100
PHASE 19b TOTAL = 4 FREE = 1 OFFLINE = 0 TYPE = HPE XL170 Intel Xeon 6252G, 48 cores, 372GB, 10ge
PHASE 20 TOTAL = 22 FREE = 0 OFFLINE = 0 TYPE = Dell R740 Intel Xeon 6238R, 56 cores, 372GB, HDR, 25ge, V100S

However, freeres shows that there are many nodes with significant number of cores/memory available on these phases:

[lngo@login001 ~]$ freeres phase18b phase18c phase19a
group file = /software/caci/cluster/phase18b
group file = /software/caci/cluster/phase18c
group file = /software/caci/cluster/phase19a
CPU | GPU | Memory (GB) |
Node Avail Used Free | Avail Used Free | Avail Used Free | State
---------------------------------------------------------------------------
node0060 40 12 28 2 2 0 376 372 4 free
node0152 40 26 14 2 2 0 376 173 203 free
node0064 40 12 28 2 2 0 376 372 4 free
node0084 40 8 32 2 2 0 376 372 4 free
node0059 40 30 10 2 2 0 376 173 203 free
node0096 40 32 8 2 2 0 376 184 192 free
node1302 40 3 37 2 0 2 376 372 4 free
node0123 40 8 32 2 2 0 376 372 4 free
node1228 40 8 32 2 2 0 376 372 4 free
node0146 40 8 32 2 2 0 376 372 4 free
node0131 40 8 32 2 2 0 376 372 4 free
node0148 40 37 3 2 2 0 376 304 72 free
node0156 40 8 32 2 2 0 376 372 4 free
node0181 40 33 7 2 2 0 376 358 18 free
node1523 40 8 32 2 2 0 376 372 4 free
node0209 40 32 8 2 2 0 376 258 118 free
node0201 40 12 28 2 2 0 376 372 4 free
node0045 40 36 4 2 2 0 754 240 514 free
node0176 40 30 10 2 2 0 376 244 132 free
node0246 40 12 28 2 2 0 376 372 4 free
node0183 40 8 32 2 2 0 376 372 4 free
node0153 40 32 8 2 2 0 754 270 484 free
node0766 40 8 32 2 2 0 376 372 4 free
node0219 40 8 32 2 2 0 376 372 4 free
node1266 40 8 32 2 2 0 376 372 4 free
node0032 40 8 32 2 2 0 376 44 332 free
node1397 40 32 8 2 2 0 376 264 112 free
node0047 40 16 24 2 2 0 376 372 4 free
node1415 40 36 4 2 1 1 376 270 106 free
node1438 40 8 32 2 2 0 376 372 4 free
node1459 40 26 14 2 2 0 376 174 202 free
node1462 40 8 32 2 2 0 376 372 4 free
node0079 40 32 8 2 2 0 376 128 248 free
node1414 40 8 32 2 2 0 376 372 4 free
node0089 40 8 32 2 2 0 376 372 4 free
node0136 40 8 32 2 2 0 376 372 4 free
node1521 40 32 8 2 1 1 376 214 162 free
node0020 40 8 32 2 2 0 376 372 4 free
node0040 40 8 32 2 2 0 376 372 4 free
node0058 40 8 32 2 2 0 376 372 4 free
node0137 40 32 8 2 2 0 376 128 248 free
node0119 40 8 32 2 2 0 376 372 4 free
node0130 40 8 32 2 2 0 376 372 4 free
checked 103 nodes in 0.42 Seconds

Taking advantage of freeres, it is possible to request portion of nodes that fit into these available resources. For example, the following qsub that specifies interconnect=25ge (to imply the usage of these nodes) is allocated in less than a minute.

[lngo@login001 ~]$ qsub -I -l select=6:ncpus=12:mem=160gb:interconnect=25ge
qsub (Warning): Interactive jobs will be treated as not rerunnable
qsub: waiting for job 4049542.pbs02 to start
qsub: job 4049542.pbs02 ready

[lngo@node0152 ~]$

Why does my program crash on login node with the message Killed?

When running commands or editing files on the login node, users may notice that their processes end abruptly with the error message Killed. Processes with names such as a.out, matlab, etc., are automatically killed on the login node because they may consume excessive computational resources. Unfortunately, this also means that benign processes, such as editing a file with the word matlab as part of its name could also be killed.

Solution: Request an interactive session on a compute node (qsub -I), and then run the application/command.

Storage Questions

How do I check how much of my paid /zfs storage allocation I am currently using?

When you buy Palmetto storage, this storage is automatically backed up every day, and the storage space that you have bought is used to store the back-up snapshots. It is very important that your owned storage is less than 90% full, otherwise backups won't work. To check how much space you are using on your bought storage, you can run the script called checkzfs from the login node. Let's say I bought 22 Tb of storage, and it's called mydata. To check it, I run

checkzfs mydata

The output will look something like this:

DATE:  2021-11-19 14:11:17.878949
============================================
USAGE FOR /zfs/mydata
Purchased: 22.0 TiB
Used: 4.7 TiB
Available: 17.3 TiB

Please leave 10% of the purchased amount for snapshots.

I can see that my storage uses 4.7 Tb out of 22 Tb, so I am good for now. I need to do it from time to time, to make sure my storage does not exceed 90% (in my case, 19.8 Tb). If it does, checkzfs will give me a warning.

Why does my folder not show up when I do ls /zfs?

We recently introduced autofs feature that automatically mounts the user directory to /zfs file system when they access it, and unmounts it after 5 minutes of inactivity. This feature increases the robustness of our file system, and will greatly decrease the visual clutter (especially important if you are accessing Palmetto through a graphical interface). Due to the automatic mounting, you will not initially see your folder in /zfs, and tab completion won't work. However, the folder is still there. You can cd directly into it, and you will not have any issues:

cd /zfs/mygroup

After you access it, you will see it when you do ls /zfs. If you won't use it for 5 minutes or longer, it will be unmounted, so next time you will have to cd into it in order to see it.

Why are my home or scratch directories are sluggish/unresponsive?

The /home and /scratch directories can become slow/unresponsive when a user (or several users) read/write large amounts of data to these directories. When this happens, all users are affected as these filesystems are shared by all nodes of the cluster.

To avoid this issue, keep in mind the following:

  1. Never use the /home directory as the working directory for jobs that read/write data. If too many jobs read/write data to the /home directory, it can render the cluster unusable by all users. Copy any input data to one of the /scratch directories and use that /scratch directory as the working directory for jobs. Periodically move important data back to the /home directory.

  2. Try to use /local_scratch whenever possible. Unlike /home or the /scratch directories, which are shared by all nodes, each node has its own /local_scratch directory. It is much faster to read/write data to /local_scratch, and doing so will not affect other users. For an example, see the local scratch documentation.

Why can't I access /software?

Typically losing access to /software means you have an Active Directory lockout on your account. You should call the CCIT helpdesk or drop by the support center in the library so they can help remove the lock and troubleshoot why it existed. A common cause is having a device with wrong credentials attempting to authenticate repeatedly on eduroam.

Once the lockout is removed you should have access to /software within an hour. If you still don't have access, please reach out to us and we can force sync the storage system.

Open OnDemand Questions

Why can't I request a bigger node or more than 8 hours?

Open OnDemand sessions provide an easy interactive experience for running various workloads for development and testing. We want to ensure users have fast access to resources so their jobs launch faster. We noticed a trend of increased wait times over earlier semesters. When investigating this trend, we discovered many interactive jobs started on Open OnDemand requested large walltimes and were not stopped after computation was complete. These idle jobs tied up compute resources that could have been better utilized by other jobs. We expect this problem to be exacerbated as we remove old CPU nodes and transition nodes to Slurm. The resource limits were put in place to encourage appropriate use of interactive jobs on Open OnDemand. This should enable faster access to resources for everyone.

This decision was also informed by examining interactive queueing policies at national HPC centers ( NERSC: Perlmutter, PSC: Bridges-2, etc.).

Node Owners

Node owners can make full use of their purchased resources and are not limited to 8 hours. Be sure to change the selected queue from work1 to your owner's queue at the top of the OnDemand form. Once changing to an owner queue, you should be able to specify custom chunk count, CPU count, memory, and walltime.

For users who need more resources or runtime, run your code as a batch job. Python scripts, Jupyter notebooks, and R scripts can all be run from a batch job. Within a batch job, you are no longer subjected to the limits shown in the Open OnDemand session creation forms, the limits are higher. Be sure to monitor your job and make reasonable resource requests. We are happy to help you create batch jobs; join us in office hours or submit a support request.

Why are Jupyter Notebooks launched through Open Ondemand are asking for a password?

This is caused by the "conda initialize" statements in your .bashrc file. Remove the following section from your .bashrc file:

# >>> conda initialize >>>
# !! Contents within this block are managed by 'conda init' !!
__conda_setup="$('/software/spackages/linux-rocky8-x86_64/gcc-9.5.0/anaconda3-2022.05-zyrazrj6uvrtukupqzhaslr63w7hj6in/bin/conda' 'shell.bash' 'hook' 2> /dev/null)"
if [ $? -eq 0 ]; then
eval "$__conda_setup"
else
if [ -f "/software/spackages/linux-rocky8-x86_64/gcc-9.5.0/anaconda3-2022.05-zyrazrj6uvrtukupqzhaslr63w7hj6in/etc/profile.d/conda.sh" ]; then
. "/software/spackages/linux-rocky8-x86_64/gcc-9.5.0/anaconda3-2022.05-zyrazrj6uvrtukupqzhaslr63w7hj6in/etc/profile.d/conda.sh"
else
export PATH="/software/spackages/linux-rocky8-x86_64/gcc-9.5.0/anaconda3-2022.05-zyrazrj6uvrtukupqzhaslr63w7hj6in/bin:$PATH"
fi
fi
unset __conda_setup
# <<< conda initialize <<<

After this section is removed, activate your conda environments with source activate.

module load anaconda3/2022.05-gcc/9.5.0
source activate <name_of_environment>

Why did my Open OnDemand job fail to launch or quit early?

View the Troubleshooting Guide for OnDemand jobs. Use the link next to the job in OnDemand (if applicable) to submit a ticket if the troubleshooting does not fix the problem.

Other

How do I fix the error undefined symbol: EVP_KDF_ctrl, version OPENSSL_1_1_1b (PBS only)?

The following answer applies to Palmetto 1 and the PBS job scheduler. This error is caused by a version mismatch between the OpenSSL that is part of the Rocky operating system, and the versions that are required by some software packages. If you get that error, please load these modules:

module load libssh/0.8.5-gcc/9.5.0 krb5/1.19.3-gcc/9.5.0

If that fails, load the anaconda3/2022.05-gcc/9.5.0 module.

Error when creating conda environment after loading anaconda module

If error occurs, please try the following command:

export LD_PRELOAD=""

Error: couldn't get an RGB, Double-buffered visual

Try running with VirtualGL.

402: Could not map pixel buffer object

Try running with VirtualGL. Make sure you specify a device to vglrun, either egl to use the EGL back end or :0.0 or :0.1 if you need to use the GLX back end.