...
cryoSPARC requires the group read/write permissions described above. As such, each member of your the lab will be able to read/write any file that is read/writable to the user ‘cryosparc_lab’. This is not necessarily bad (assuming there is a certain level of trust amongst all lab members); for example, if UserA is running cryoSPARC calculations in /athena/xyzlab/scratch/userA/cryosparc_stuff, then UserB could delete this entire directory if they wished. One way to limit this exposure is for you to create a specific directory for which to run cryoSPARC calculations in (thereby isolating group access). Once the calculations are complete, you could conceivably move the completed results into a more restricted directory (however, you should read the documentation carefully about migrating projects, as I don’t know how cryoSPARC2 how cryoSPARC will respond to this if additional work was needed). However, assuming everyone in the lab is nice/behaves ethically, you don’t have too worry much about this.
...
It’s clear for most jobs whether they require GPUs or not (obviously, if the calculation has an input for the # GPUs available, then it needs GPUs!). However, some are ambiguous. We recommend you assume that the calculation does not require GPUs (if it’s not clear) and submit to `cryo-cpu`. If the calculation does require GPUs, it will almost immediately error out complaining about `pycuda`—if you see this, just clear the job and submit to a GPU-queue. If trial-and-error is not your thing, I’m sure the cryoSPARC2 documentation describes the cryoSPARC documentation describes this in detail for each calculation
...