Users may experience the following error when running Podman or Docker:
Error: pasta failed with exit code 1: Failed to open() /dev/net/tun: No such device Failed to set up tap device in namespace
This error is caused by our recent security mitigation that blocks the tun kernel module to protect against a Linux vulnerability. Once RHEL releases an official patch, this issue will be fully resolved.
The license server hosted by OSU Arts and Sciences is currently inaccessible by our clusters. This results in frame renderer being unable to render frames at all, or without watermarks depending on the render
We are working with OSU to resolve this issue
We have identified a potential performance regression in point-to-point communication when using NCCL version 2.29 on the Ascend and Pitzer clusters, which results in a 15% to 25% performance drop.
If you experience performance regression on Pitzer or Ascend, please switch to NCCL version 2.23.4.
Linaro MAP can fail to work in linaro-forge/23.0.4
We recommend to use linaro-forge/25.1.3 instead
After the scheduled downtime on May 12, 2026, STAR-CCM+ has been encountering out-of-memory errors when running OpenMPI jobs. A message similar to the following appears repeatedly in the output:
[c0317.ten.osc.edu:1736021] Read -1, expected 133860, errno = 1
We have not yet identified the root cause of the issue; however, we have discovered that this error does not occur in multi-node jobs.
As of the downtime on 05/12/26 MATLAB (legacy) has stopped working when users try to open .m files in the GUI application for version r2024a. At the time we suggested to please use the server based MATLAB option underneath "Interactive Apps" > "Servers" > "MATLAB". Or, use any version other than MATLAB (legacy) r2024a
This has since been resolved
autodock-gpu/1.5.2 does not work on Cardinal. We suggest using autodock-gpu/1.6 instead
If you have classroom projects at OSC that used the Jupyter or RStudio apps through class.osc.edu before June 30, 2025 and plan to reuse your classroom environment, the PI will need to complete the following one‑time update:
Users have reported that running Wine32 (32-bit Wine) results in a Segmentation fault (core dumped). The issue is linked to how cgroups (control groups) are handled or enabled on specific compute nodes or environments.
When trying to run starccm on a vis node in order to use GPU for visualization (not for GPU calculation), the typical way to do this would be to load the virtualgl module and use vglrun
module load virtualgl/3.1.1
module load starccm/19.06.009
vglrun starccm+
However, starccm does not pick up libraries from $LD_LIBRARY_PATH by default, so it does not pick up the necessary graphics libraries
