Introduction for new users and students

This wiki is a collaborative initiative by the department to facilitate peer knowledge exchange. Users are encouraged to extend and update the information on this website.

As part of our department, at some point you will likely need to use one our imaging systems, access patient e-health records or do a presentation. For a high-level overview to help you navigate your options see here.

New student or staff

This wiki may serve as a reference for using certain softwares and computer systems. A few notes on usage:

• The preferred language is English but pages may also use Chinese. The markup language used by this site is called Wikitext.
• Use the search bar at the top of the page to query specific keywords.
• If a page doesn't exist, creating a new page and back-linking to other articles is easy.

In addition the wiki, the department runs a few other cloud services, such as:

• Our own Gitlab, for all staff/students
• Our high performance computing cluster.
  • You can also use this for storage, but staff/students typically already have a large GoogleDrive or OneDrive.
• An Rstudio Server (Experimental)
• A research PACS server (Under development)

If there's interest, the wiki scope may be expanded to a general department resource, e.g. including student study guides, educational materials, or social events.

New HPC user

What and Why

There are many websites introducing and explaining the concepts of high performance computing. To quote a page from Iowa state university:

 "An HPC cluster is a collection of many separate servers (computers), called nodes, which are connected via a fast interconnect."

For novice users it may not be necessary to learn everything about using the hpc cluster, depending on your use-case:

• You only want to store/backup data on our storage node
• You want to run a remote desktop GUI, e.g. MATLAB or a dicomviewer
• You want to run a webserver, e.g. a Jupyter Notebook or Tensorboard instance
• You want to run a non-interactive script

Using our cluster

If you wish to use our hpc cluster, please create an account. If you are already familiar with working on a remote Linux system you probably only need to consult the GPU cluster page. Your write access is typically restricted to non-critical folders, so don't be afraid to break anything.

Most uses will require you know how to connect to an interactive shell session over SSH. See our guide on shell basics.

Visitors

Please refer to our main department website at radiology.hku.hk for contact details.