No Space Left
If you see a 'No Space Left' or a similar message (no quota remaining, etc) check the path(s) in the error message closely to look for 'home', 'orange', 'blue', or 'red' and check the respective quota for that filesystem. All quota commands are in the 'ufrc' environment module and include 'home_quota', 'blue_quota', 'orange_quota'. See Getting Started and Storage for more help.
A convenient interactive tool to see what's taking up the storage quota is 'ncdu' in the 'ufrc' env. module.
Q: I want to have a custom install of an application or python modules.
A: We recommend creating a Conda environment and installing needed packages with the 'mamba' tool from the conda environment module. It is possible to mix conda and pip installed packages inside a conda environment as conda/mamba is aware of packages installed via pip, but not vice versa.
Q: Installed a python package via 'pip install something', but 'import something' results in an error.
A: A pip install you performed puts the resulting package into your personal directory tree located in the ~/.local/lib/pythonX.Y/site-packages directory tree. A personal pip install can often result in an installation of a python package from a binary archive (wheel) that was built on a system against software libraries that are not compatible with HiPerGator. A typical error message in such case complains about the lack of a particular GLIBC version or some other missing library. Note that the issue can be exacerbated by an incompatible interaction between an environment loaded via an environment module ('module load something') and a personal python package install. To avoid this issue the python package must be installed into an isolated environment. Our approach for creating such environments depends on many factors, but usually results in a Conda or containerized environment.
Q: Why is my job still pending?
A: According to SLURM documentation, when a job cannot be started a reason is immediately found and recorded in the job's "reason" field in the squeue output and the scheduler moves on to the next job to consider. Please refer to "Why is my job not running" for a list of reasons.
Q: Why is HiPerGator running so slow?
A: There are many reasons why users may experience unusually low performance while using HPG. First, users should ensure that performance issues are not originated from their Internet service provider, home network, or personal devices.
Once the possible causes above are discarded, users should report the issue as soon as possible via the RC Support Ticketing System. When reporting the issue, please include detailed information such as:
- Time when the issue occurred
- Nodes being used, i.e. username@hpg-node$. Note: Login nodes are not considered high performance nodes and intense jobs should not be executed from them.
- Paths, file names, etc.
- Operating system
- Method for accessing HPG: Jupyterhub, Open OnDemand, or Terminal interface used.