An app on UCloud is a pre-configured research environment running inside SDU’s secure infrastructure.
Apps can be interactive (e.g., Chat UI, Coder, Transcriber) or batch-based.
When you start an app, you are launching a compute job on Interactive HPC.
A job is a running instance of an application.
When you launch an app, UCloud allocates CPU, memory, and optionally GPU resources for you.
You can monitor, stop, or restart your jobs from the Jobs page.
Workspaces on UCloud can be switched by using the workspace selector. It is a blue button, found in the top right corner. Switching workspaces updates UCloud pages with the appropriate allocations, job history and options for collaboration.
A personal workspace is called "My workspace" on UCloud and is your individual working area. The granted 2000 core-hours for this workspace are reset annually at tthe end of May.
It is intended for your own experiments, development tasks, and smaller activities.
A project workspace is a shared environment connected to a specific research or teaching project. It is created by applying for resources and receiving grant approval.
It allows multiple members to collaborate, share storage, and use allocated compute resources (CPU/GPU) under a common project framework.
If the requested resources are currently in use (for example GPUs), your job will wait in queue until resources become available.
Once scheduled, it will automatically start.
Yes.
Most apps allow you to use the terminal to:
Install additional software packages
Add extensions
Configure your environment
You can also launch Linux-based environments and build your own setup from scratch.
You need to apply for GPU resources for a project workspace and when they are granted, in the job submission page, the option to select a machine type with GPU will become available.
Closing the browser does not stop the job.
Interactive apps continue running until:
You stop them manually, or
The allocated runtime expires
Always stop unused jobs to free shared resources.
Yes.
All applications run inside SDU’s data center under institutional governance and data processing agreements.
Data processed in UCloud:
Is not used to train external AI models
Is not shared with commercial third parties
Remains within university-controlled infrastructure
This makes UCloud suitable for research and teaching involving sensitive or restricted data.
Yes.
UCloud is used for:
Teaching environments
Course-specific projects
AI-supported learning
Programming and data science exercises
Access depends on project membership and resource allocation. Students can get access to additional and other types of resources beyond those available in "My workspace" through their supervisors, who manage UCloud projects for teaching or course projects.
UCloud supports:
Data analysis tools
Machine learning frameworks
AI language model interfaces
Development environments
Linux-based custom environments
Traditional batch compute applications
A full indexed list is available on the Applications page.
Documentation is available directly from:
Each app’s dedicated UCloud page
You’ll find guides on launching apps, submitting jobs, monitoring resources, and best practices.
Tutorials are available here: Tutorials – Interactive HPC
