RStudio

We have private and shared RStudio instances for researchers as a service. It is available from a RStudio portal that also points to dedicated teaching and individual researcher instances. This portal and those instances can also be accessed from outside of UC. Request for access should be sent to the eResearch support team via the button below and stating that you want to use the eResearch RStudio in the "Other information" box. Other optional fields can be left blank or to their default.

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 up to a point for RAM and CPU. 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 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, using the button above, to the best of your abilities 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 central Research Compute Cluster (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 under the name "CRCResearch" (historical name for the first project requesting a large memory instance).

To request access please fill a RCC project request using the button above 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 use this form 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.