We recently got a supercomputer (I will call it the "cluster", it has 4 GPUs and 12-core processor with some decent storage and RAM) to our lab for machine learning research. A Linux distro (most possibly CentOS or Ubuntu depending on your suggestions of course) will be installed in the machine. We want to design the remote access in such a way that we have the following user hierarchy:
- Admin (1 person, the professor): This will be the only superuser of the cluster.
- Privileged User (~3 people, PhD students): These guys will be the more tech-savvy or long-term researchers of the lab that will have a user defined for themselves at the cluster. They should be able to setup their own environment (through docker or conda), remote dev their projects and transfer files in and out of the cluster freely.
- Regular User (~3 people, Master's students): We expect these kind of users to only interact with the cluster for its computing capabilities and the data it stores. They should not have their own user at the cluster. It is ok if they can only use Jupyter Notebooks. They should be able to access the read-only data in the cluster as the data we are working on will be too much for them to download it locally. However, they should not be able to change anything within the cluster and only be able to have their notebooks and a number of output files there which they should be able to download to their local system whenever necessary for reporting purposes.
We also want to allocate only a certain portion of our computing capabilities for type 3 users. The others should be able to access all the capabilities when they need.
For all users, it should be easy to access the cluster from whatever OS they have on their personal computers. For type 1 and 2 I think PyCharm for remote developing .py files and tunneling for jupyter notebooks is the best option.
I did a lot of research on this but since I don't have an IT background I cannot be sure if the following approach would work.
- Set up JupyterHub for type 3 users. This way we don't have to have these guys to have a user at the cluster. However, I am not sure about the GPU support of this. According to here, we can only limit CPU per user. Also, will they be able to access the data under Admin's home directory when we set up the hub or do we have to duplicate the data for that? We only want them to be able to access specific portions of data (the ones related to whatever project they are working on since they sign a confidentiality to only that project). Is this possible with JuptyterHub?
- The rest (type-1 and type-2) will have their (sudo or not) users at the cluster. For this case, is there UI to workaround so that users can more easily transfer files from and to the cluster (that they don't have to use scp)? Is FileZilla an option for example?
- Finally, if the type-2 users can resolve the issues type-3 users have so that they don't have refer to the professor each time they have a problem. But afaik, you have to be a superuser to control stuff at JupyterHub.
If anyone had to setup this kind of an environment at their own lab and share their experiences I would be grateful.
