Private RStudio server instance
eResearch services can deploy private RStudio server instance for researchers. The server runs ubuntu underneath and can be tailored to your needs in terms of RAM and cpu to some extent. Note that if you have a large memory requirement (more than 64GB of RAM) we provide a specific instance for these workloads, see in the next section.
Your RStudio server will be made available from the RStudio portal at https://rstudiorcc.canterbury.ac.nz/ with a name of your choosing. While most servers use UC credentials for username and password, this can be tailored. To request an instance, fill a project form to the best of your abilities at https://services.canterbury.ac.nz/uc?id=sc_cat_item&sys_id=36ff8910dbda0510e447f561f3961969 and indicate RStudio as the software you want to use. A consultant will then be in touch with to fill any gaps in your request and organise the delivery of the instance.
Big R
We have a large memory instance of RStudio on the RCC. The instance has the following
- 384GB of RAM
- 32 cpus
- ~2TB of disk - expandable to some extent to accommodate your projects
The underlying server is ubuntu and R/RStudio are regularly updated. Updates can be requested as needed. People are expected to install their own packages but installing non-R packages needed for a R package can be requested.
Access is on request with your UC usercode and password from the rstudio portal at https://rstudiorcc.canterbury.ac.nz/ under the name "CRCResearch" (historical name for the first project requesting a large memory instance).
To request access please fill a RCC project request at https://services.canterbury.ac.nz/uc?id=sc_cat_item&sys_id=36ff8910dbda0510e447f561f3961969 and indicate that you want to use the big R instance, you can leave the fields for "Operating System", "CPUs", "Memory size" and disk blank or on their default. Please do indicate if you want to bring or produce data in volumes larger than 500GB.
Request for update and package installation should go to https://services.canterbury.ac.nz/uc?id=sc_cat_item&sys_id=7be2c74cdb160510e447f561f396196a and select "eResearch" as the area your request relates to. Please mention that the request is about big R in the body.
The size of the data that can be uploaded via the web interface is limited. If you have large data there are alternate way of accessing it. If it sits on a UC research drive, we may be able to make it directly accessible to you. In other cases you can transfer data directly to the big R machine using sftp/rsync or scp. For this to work, you have to be on campus or connected to the campus network via VPN as the machine is not directly accessible from the wider internet for this kind of access. You can point your transfer program (fileZilla which is available on windows for example) to 132.181.102.56. In the case of fileZilla, be sure to select "sftp" as the protocol as "ftp" is the default.