Categories
Interactive HPC Research Supercomputing UCloud Use case

Combining AI and satellite data to explore the upper atmosphere

For researcher Lotte Ansgaard Thomsen at Aalborg University, UCloud has played a central role in the research project UpperAtmosphere, where she combines artificial intelligence, satellite data and physical models to better understand conditions in the upper atmosphere.

Many satellites operate in this part of the atmosphere, where conditions can change quickly due to solar activity. However, traditional physical models do not always capture these rapid changes accurately. To address this, Lotte uses AI to learn patterns from different data sources and improve the physical model.

Lotte Ansgaard Thomsen is an Associate Professor in the Department of Sustainability and Planning at Aalborg University. In her current research project, she investigates how AI can be used to improve the understanding of key variables in the upper atmosphere. This can contribute to more accurate models of the space environment where satellites operate and provide better insight into the conditions that may affect satellite performance, communication systems, and space-based infrastructure.

Combining AI and physical models

A key part of the project is the combination of several different data sources. Satellite measurements, solar activity data and ionospheric data each contribute with important information. When these data sources are used together, the AI model can improve the physical model significantly. According to Lotte, this combination is one of the central insights of the project so far:

“A key insight is combining different data sources really matters. Satellite measurements, solar activity, and ionospheric data each add something unique. When I use them together in AI on top of the physical model, the model improves significantly.”

Using UCloud as the primary platform

Lotte has used UCloud as the primary platform for running the computational work in the project. A large part of this involves training AI models, which requires substantial computing power because the datasets are large and the models need many iterations to find the right architecture. However, UCloud has not only been used for the heavy computations at the end of the process. It has also supported the development and testing of code along the way.

“It gives me a good environment to build the workflow, try things out, and adjust as I go.”

Lotte also uses UCloud in another research project, where large language models are used to work with environmental data. Across both projects, access to computing power has been essential.

“In both projects, we simply could not have done the work without access to this kind of computing power or a similar alternative.”

Access to computing power made results possible faster

When Lotte moved from industry into academia, she was concerned about whether she would have access to enough computing power for her research. Discovering that UCloud existed was therefore an important advantage.

“It was really nice to discover that UCloud existed. Having access to that number of resources has been a big advantage for the project.”

With UCloud, Lotte could access the computing power needed without first having to apply for separate funding. This made it possible to move faster from development to results.

“If I did not have access to UCloud or another free service, and first had to apply for funding just to get compute, it would have been impossible to have results so fast.”

A user-friendly platform for research

According to Lotte, one of the main benefits of UCloud is its user-friendly setup for research and development work.

“First of all, UCloud is really well-suited for development work. It gives me a good environment to build and test my workflow, and for research work, I have found that it has a very user-friendly interface.”

She has used Visual Studio Code, a code editor used for writing, testing and developing code, on UCloud, which gives her a setup similar to the one she uses locally. This makes it easier to move between local development and cloud-based work. Another important advantage has been the possibility to scale up and access more compute when needed.

“It has been very easy to scale up and get more compute when I need it.”

Fast support makes a difference

For Lotte, the support around UCloud has also been an important part of the experience. When working with complex research projects, technical issues can slow down the research process. In her experience, the support team has responded quickly when challenges have occurred.

“If I run into any issues, the team helps almost immediately. That makes a big difference when working on complex projects.”

Lotte has received support from Aalborg University’s local front office, which helps researchers get started with UCloud and provides support when questions or technical issues arise. All Danish universities have a local front office where researchers can get support.

Overall, UCloud has provided Lotte with access to the computing resources, development environment and support needed to work with large datasets, AI models and complex research workflows.

“I think UCloud is a really good solution overall. When people talk about the need for more European cloud alternatives, this is the kind of thing I think of.”

This work was supported by DeiC National HPC (g.a. DeiC-KU-L1-291125). Read more about DeiC’s calls for resources on HPC-platforms: Grants og funding | DeiC.

Categories
Application Call Interactive HPC Research Supercomputing UCloud

H1-2027: National HPC call opens on 21 July 2026

You can now apply for compute time on UCloud. DeiC has opened the second 2026 call for applications for access to Denmark’s national HPC facilities. So if your research needs extra compute resources on UCloud, now is the time to apply.

These calls only open twice a year, so this is a great opportunity to consider applying in this round. Researchers (and PhD students) at Danish universities can apply.

Key dates

  • Call opens: 21 July 2026
  • Call closes: 1 September 2026
  • Resources available: 1 January 2027

Read more and apply via DeiC

Categories
Research Supercomputing UCloud Use case

Danish language model project enters a new phase with stronger national computing power

How do we ensure that the artificial intelligence of the future understands the Danish language, Danish institutions, and Danish society – while handling data within frameworks that we control ourselves?

This question lies at the heart of the research project Danish Foundation Models (DFM), where the University of Southern Denmark, Aarhus University, the University of Copenhagen, and the Alexandra Institute are collaborating to develop open Danish language models. The project has been underway for some time, and researchers have already released the first models, established benchmarks, and initiated collaborations with external partners. Now, the project is entering its next phase.

With access to the new national AI supercomputing facility BITTEN, inaugurated in Sønderborg in May, and accessible through the research platform UCloud, the pace of development can increase significantly.

Culture, norms, and societal understanding are lost

Within just a few years, language models have become a strategic technology. They are already used for text generation, search, decision support, automation, and analysis. However, the most widespread models have been developed by global companies and trained primarily on English and other major languages.

This creates limitations when such models are expected to operate within a Danish context.

“If you look closely at the details, many international models are actually poor at Danish. The way they formulate themselves often resembles English translated into Danish. That is not how we speak or write,” says Professor Peter Schneider-Kamp from the University of Southern Denmark, who leads DFM on behalf of SDU.

The challenge extends beyond language. It also concerns culture, social norms, and an understanding of society.
DFM has, among other things, developed Danish benchmarks that test models on knowledge of Danish culture. Here, even the largest international models often perform poorly.

“They lack an understanding of how Denmark works – our literature, our public institutions, our healthcare system, and our cultural points of reference,” Schneider-Kamp explains.

Denmark cannot remain on the sidelines

The development of AI is moving so rapidly that access to domestic expertise and infrastructure is becoming increasingly important. According to Schneider-Kamp, it is risky to assume that other countries will continue to provide the services and models that Europe needs indefinitely.

“We cannot simply rely on American or Chinese companies to provide the right solutions for us forever. We need to take part in the development ourselves,” he says.

This is not about replicating Silicon Valley at the same scale, but about being able to develop solutions tailored to Danish needs – and doing so on a transparent and responsible foundation.

“We want models where we know what they have been trained on, that comply with GDPR and the AI Act, and that understand the Danish language, Danish culture, and Danish norms,” he says.

UCloud is the backbone

Behind the project lies a less visible, but crucial part of the story: research infrastructure.

DFM is developed to a large extent using UCloud, the national platform for interactive high-performance computing developed by SDU eScience Center together with partners. It provides researchers with access to storage capacity, GPUs, software, and collaboration tools in one integrated environment.

For Peter Schneider-Kamp, UCloud is absolutely central.

“UCloud is our secure environment where we develop models, train models, store data, and evaluate them. It is absolutely central to everything we do,” he says.

The security perspective is essential. When researchers work with large amounts of data – and in some projects also sensitive data – it is critical that the data can be handled within a controlled environment.

“If we receive new datasets from, for example, libraries, media organisations, or other sources, we can store them securely, work directly on them, and maintain control over the data,” he says.

The alternative is often more complex and fragmented solutions where data has to be moved between systems and countries.

New national supercomputer BITTEN

On 5 May 2026, a new national supercomputer was inaugurated in Sønderborg: BITTEN. The facility was established by the University of Southern Denmark in collaboration with Danfoss and Hewlett Packard Enterprise (HPE) and forms part of the Danish research infrastructure for artificial intelligence, advanced computing, and data-intensive research.

The supercomputer is made available through UCloud, allowing researchers and students at universities across Denmark to access it through their existing systems and workflows.

The collaboration combines SDU’s experience in research infrastructure, Danfoss’ expertise in energy-efficient cooling and heating solutions, and HPE’s knowledge of supercomputing and data centre technology.

The facility has also been designed with a strong focus on energy-efficient operation and the reuse of excess heat.

Lack of computing capacity slows down research

For AI research, access to computing power is not a luxury – it is a prerequisite.

Previously, the DFM group regularly experienced bottlenecks when training models.

“Sometimes we have had to wait two, three, four, or even five days to get access to a GPU. Meanwhile, PhD students and postdoctoral researchers are sitting ready with ideas and code but are held back by a lack of resources,” says Peter Schneider-Kamp.

This is precisely where the new capacity can make a difference.

More computing power means faster experiments, larger models, more iterations, and a shorter path from idea to result.

“We hope it will allow us to turn ideas into research results and concrete use cases much faster. We are incredibly excited to gain access to the many additional GPUs,” he says.

More than technology

DFM is therefore about more than software and hardware. The project illustrates how research, digital sovereignty, data security, and innovation are closely connected.

If Denmark wants to use AI in healthcare, the public sector, education, and industry, it requires solutions that can be understood, adapted, and trusted.

With UCloud as its operational backbone and the new national supercomputing capacity of BITTEN, Danish Foundation Models now stands at a point where the work can move from a promising development phase to broader implementation.

The question is no longer only whether Denmark can develop its own language models.

The question is whether we can afford not to.

Categories
Supercomputing UCloud UCloud status

Successful data centre migration brings more GPU power and simpler access to UCloud

The migration of the SDU data centre from SDU’s campus in Odense to the Danfoss premises in Sønderborg has been completed successfully. The migration was a result of several months of careful planning in close collaboration with the many stakeholders involved. It was scheduled to take place over the course of one week and was completed fully within that timeframe. 

More GPU power, simpler access and new possibilities in UCloud 

As part of the new setup, UCloud has been upgraded with new features and a more powerful infrastructure. The changes give users better access to modern computing resources, a simpler user experience and new options for working with both applications and virtual machines. 

The new system is designed to make it easier for you to get started, while also providing significantly more computing power for demanding tasks such as AI, machine learning, data analysis and advanced HPC workloads. 

More GPU capacity 

The new UCloud setup significantly increases the available GPU capacity. The platform now includes 128 full NVIDIA B200 GPU cards, which is around three times as many as before. In addition, the new B200 cards are more powerful than the GPU cards they replace. 

This means that more GPU resources are available in one place, improving availability across the system and making it easier for users to access the computing power they need. 

The NVIDIA B200 is among the most advanced GPU cards currently available and is designed to support the most demanding HPC and AI workloads. Users working with large models, complex computations or data-intensive workflows will therefore have access to more powerful hardware than before. 

More affordable GPU access with MIGs 

A new option in UCloud is the possibility of using Multi-Instance GPUs (MIGs). With MIGs, a single GPU is divided into smaller, fully isolated GPU instances. This makes it possible to use part of a GPU instead of a full B200 card. One MIG corresponds to 1/7 of a full GPU card. 

This means that users can access GPU resources for one seventh of the price of a full GPU. For many tasks, this offers an ideal trade-off. If a workload does not require the full power of a B200 GPU, MIG provides access to GPU acceleration at a much lower cost. 

This can help users get more out of their budget. By choosing a MIG GPU instead of a full GPU, an allocation can last for more hours, making it possible to run more jobs within the same budget. 

At the same time, MIGs helps improve availability across the system. Because several users can share the capacity of a single GPU, more users can access GPU resources at the same time. 

A simpler system with one provider 

The new UCloud setup is also simpler to use. Instead of choosing between several different providers, most users will now work with just one provider. 

This makes the user experience clearer and reduces the amount of technical knowledge required to get started. It becomes easier to understand where to run workloads and which resources to choose. 

The new provider setup also means that users work in a secure environment that is approved for handling sensitive data.  

For users, this means less time spent understanding the infrastructure and more time spent on their actual research, analysis or development work. 

New virtual machine options 

UCloud now also includes new virtual machine options. These provide better integration between virtual machines and the other applications available in UCloud. 

This makes it easier to combine workflows where some tasks run as applications and others require a virtual machine environment. For users who need more flexibility, custom software setups, higher system privileges, or longer-running environments, the new virtual machine options provide more ways to work in UCloud. 

The new virtual machines also support persistent storage. This means that users can pause and resume machines without losing their working environment or stored data. 

This provides a more flexible way of working. Users can set up an environment, pause it when they do not need it, and continue from the same point later. 

Easier connection between jobs 

UCloud also introduces a new way to connect jobs. It is now possible to create a local network between jobs, making it easier for different parts of a workflow to communicate with each other. 

Previously, users could be more dependent on the order in which applications were started. With the new local networking option, your jobs can be connected in a more flexible way. 

If you have any questions about the new data centre setup or how it affects your work in UCloud, please reach out to your local front office

Categories
Interactive HPC Research Supercomputing UCloud Use case

How UCloud supported large-scale research combining time-use and consumption data to understand socio-economic differences 

 UCloud played an important role in Sofia Topcu Madsen’s research by helping her analyse large-scale time-use and consumption data across seven countries faster and more efficiently, supporting her work to gain insights into how people spend their time and money in everyday life. 

Sofia Topcu Madsen is a former PhD fellow at Aalborg University, Department of Sustainability and Planning. As part of her PhD project, Getting the Data Right, she investigates how people across seven countries in low- and middle-income countries spend time and money on different everyday activities — and how socio-economic factors shape what people are able to do. 

The project looks at countries including Uganda, Kenya, Tanzania, India, Sri Lanka, Argentina and Mongolia. Based on large-scale time-use and consumption data, Sofia analyses activities such as transport and household work and explores how time and money spent on everyday activities vary across different socio-economic groups. 

Working with large datasets 

Sofia’s analyses are based on different types of detailed data. One example is time-use diaries, where participants report what they do throughout the day in 10-minute intervals. For some countries, the datasets are very large. In the Indian dataset alone, Sofia works with around half a million observations. 

This makes the computational work demanding. At first, Sofia tried running the analyses on her own computer, but the datasets were too large and the analyses too time-consuming. 

“On my own computer, the analyses could take several days to run. With UCloud, it became much faster and more manageable,” Sofia explains. 

UCloud gave her access to more computing power, making it possible to run large analyses more efficiently and rerun them when corrections or adjustments were needed. This became important throughout the project, as even small changes in the data setup or model specification could require the analyses to be run again. 

“UCloud has been a huge help. I do not think I would have been able to complete this part of the project in the same way without access to it,” Sofia says. 

Using Stata and R on UCloud 

To conduct the analysis, Sofia used Stata and R on UCloud. Stata and R are tools that researchers use to work with data and carry out statistical analyses. 

In Sofia’s project, the tools were used to run regression analyses, where she examines how different factors may be connected — for example how education, income or gender may relate to the amount of time and money people spend on transport, household work or other everyday activities. 

She used SUR methods, which make it possible to run several related analyses at the same time. This was relevant because the project looks at activities across a full 24-hour day, where time spent on one activity can be connected to time spent on another. Similarly, money spent on products supporting one activity limits money for other products. 

Running several analyses at the same time with large datasets requires a lot of computing power and would have been very time-consuming to do on a normal computer. By using UCloud, Sofia could run the analyses faster and more efficiently, saving her a lot of time. 

Contributing to research on sustainable development 

Sofia’s research is connected to the UN Sustainable Development Goals by exploring how everyday activities can be used as indicators of broader social and economic conditions. 

How people spend their time can tell us something important about everyday life, inequality and opportunities. For example, a joint perspective on time and money spent on transport, household work, or leisure can reveal how resources, responsibilities, and opportunities are distributed across different population groups. 

“Time can also be understood as a resource. Looking at how people spend their time gives us another way to understand poverty, inequality and sustainable development,” Sofia explains. 

A platform that was easy to get started with 

Sofia describes UCloud as easy to access and use, especially once the workflow was in place. She also highlights the support as an important part of the experience. 

“The support has been very effective. I have received quick answers to my questions, and that has been a big help,” she says. 

Sofia received support from Aalborg University’s local Front Office. Each Danish university has its own Front Office, where researchers can get help with access, use and questions related to UCloud. 

Would use UCloud again 

Sofia is now employed at the University of Copenhagen, Department of Food and Resource Economics, and she can see herself using UCloud again in future research. 

“I would definitely use UCloud again,” she says. 

Because UCloud is available to researchers affiliated with Danish universities, Sofia can also continue to use the platform in future research projects at the University of Copenhagen. 

Categories
Interactive HPC UCloud UCloud status

New data centre for UCloud – what does it mean for you? 

A new data centre for UCloud will open soon. As part of the transition, there will be a period of downtime at the end of April/beginning of Mayand – for some users – a need to move data.

The data centre is being established through a collaboration between SDU, Danfoss and Hewlett Packard Enterprise (HPE) and will host the hardware behind DeiC Interactive HPC – UCloud. At the same time, the infrastructure is being upgraded with new and more powerful hardware.

The UCloud infrastructure will therefore be consolidated in a single data centre instead of being distributed between SDU and AAU. The transition may affect you as a user. Here is an overview of what you should be aware of.

Short downtime during the migration

When the system is migrated to the new data centre at the end of April 2026, all services will be temporarily unavailable until the migration is complete. The new data centre is expected to be fully operational in early May 2026. Exact dates and further details are available in the UCloud documentation.

Moving data

If your data are stored in SDU/K8s, they will be moved automatically to the new data centre during the migration. You do not need to take any action.

⚠️ Special note for users with data in Aalborg (AAU) ⚠️

If you have data in AAU/K8s or AAU/VM, they will not be moved automatically. These data must be transferred to SDU/K8s before 27 April 2026, otherwise they will be lost. Please note that transferring data can take time, so it is a good idea to plan accordingly.

Go to the guide on how to move your data.

All compute allocations will expire

As part of the transition to the new system, all existing compute allocations will expire on 30 April 2026. This happens automatically as part of the migration to the new infrastructure.

Procedures may vary between universities

The procedure for new allocations on the new data centre is determined by your university, and the allocation of compute resources is handled by the university’s local DeiC front office.

If you are unsure about the procedure, we therefore recommend contacting your local DeiC front office.

For further information, important dates and the timeline, see UCloud’s documentation.

More computing power – and a simpler system to use

In the new data centre, UCloud will receive new and more powerful hardware, giving researchers better opportunities to work with large datasets, advanced computations and AI.

At the same time, it will become easier to choose the right resources. Where several different machine types were previously available, users will now simply choose between two types of compute:

  • CPU – for standard computations
  • GPU – for tasks such as AI and advanced data processing

This simpler structure makes it quicker and clearer to apply for and use computing power, allowing researchers to focus more on their analyses and less on technical choices.

The new data centre has also been designed with a focus on energy-efficient operation. In collaboration with Danfoss and HPE, advanced cooling and heat recovery systems are used that make it possible to reuse excess heat and reduce energy consumption.

The initiative forms part of ProjectZero in Sønderborg, which is working to make the area’s energy system CO₂-neutral by 2029.

Read more about the new data centre here:

Categories
Interactive HPC Supercomputing UCloud

New Agreement Strengthens Collaboration on DeiC Interactive HPC

Shortly before Christmas 2025, DeiC and the Interactive HPC Consortium entered into a new five-year agreement on the national HPC service, with an annual budget of DKK 10 million. At the same time, the DeiC Board decided to invest a one-off amount of DKK 4 million in expanded GPU capacity. This additional investment has made it possible to significantly upgrade the facility. The upgrade strengthens opportunities for research projects working with large datasets and AI, while also providing better opportunities to use GPU resources more broadly.

In spring 2026, the consortium will establish a new energy-efficient data centre that will house the hardware for DeiC Interactive HPC. Danfoss and HPE are participating in the establishment of the data centre, which is described here.

“Through the new agreement, we are strengthening a shared national research infrastructure that gives researchers across Denmark easy access to advanced computing power. This is an important step for both digitalisation and digital sovereignty in Danish research. At the same time, the collaboration between the universities demonstrates that we can jointly develop solutions that are both technologically strong and sustainable – not least through the establishment of an energy-efficient data centre,” says Professor Claudio Pica, coordinator of the Interactive HPC Consortium.

Collaboration and development in focus

With the new contracts, DeiC and the Interactive HPC Consortium continue and expand a strong and trusted partnership. The long-term nature of the agreements and the strengthened financial framework reflect a solid collaboration and a shared commitment to developing the solution in close dialogue with users and DeiC’s professional forums. The aim is a solution that evolves in line with researchers’ needs and priorities.

At the same time, the agreements build on the service’s high level of security and strengthen the already well-established framework for reporting on usage and operations. Finally, the partners have established clear shared expectations regarding the handling of future development work and system integrations.

Acting Head of HPC at DeiC, Rune Gamborg Ørum, sees the new agreement as an important step forward:

“Beyond the opportunities offered by the new facility itself, I am pleased that our joint work on the contracts has also created a clear collaborative structure around the service. This will make a real difference for users, as it allows us to work together to support the many different ways researchers use DeiC Interactive HPC.”

In February 2026, the partners met in Aarhus for a joint workshop focusing on putting the agreement into practice and ensuring a well-functioning collaboration on technical development, user support and training activities in the coming years. Among other things, participants discussed how existing users can transition smoothly to the new data centre and the new GPU resources.

DeiC Interactive HPC 

DeiC Interactive HPC provides interactive and user-friendly supercomputing for researchers at Danish universities. The service is based on the UCloud platform, operated by the Interactive HPC Consortium consisting of the University of Southern Denmark (SDU), Aarhus University (AU) and Aalborg University (AAU).

Today, DeiC Interactive HPC has approximately 22,000 users among students and researchers and supports a wide range of research fields. Through DeiC Interactive HPC, DeiC and the universities provide researchers across the country with access to scalable computing power via UCloud.

Categories
Interactive HPC Research Supercomputing Teaching UCloud Use case

UCloud Provides Student Access to Advanced NLP in Teaching 

In the Master’s programme in Cognitive Science at Aarhus University, UCloud plays a central role in teaching Natural Language Processing (NLP). For instructor and PhD student Mina Almasi, the platform is essential in enabling students to work hands-on with complex models – regardless of the limitations of their own computers.

From Theory to Hands-On Learning 

In a white classroom in Nobelparken, Mina stands in front of 15 students. On the screen behind her, lines of Python code appear in neat, symmetrical rows as she explains which code libraries the students need to access.

In her teaching, she uses the Coder Python application in UCloud because the course is based on Python programming. But the choice of platform is not just about software – it is about giving students the opportunity to translate theory into practice.

According to Mina, NLP teaching previously tended to remain at a more theoretical level, due to limited access to both models and the computing power needed to test theories in practice – especially when it came to large language models. With UCloud, students can now work directly with language models (LLMs) and make use of powerful GPUs and CPUs. This allows them to test theories themselves and experiment hands-on with the tools they are learning about.

“We still teach the theory, but now we can also have students use the tools in practice. They can code on their own and gain insight into how a large language model works by working directly with it through UCloud,” she explains.

A Standardised Setup that Democratises the Classroom 

Another advantage of using UCloud in NLP teaching is that the platform ensures equal access for all students, regardless of the computer they own.

“There is a kind of democratisation of the classroom, because you don’t need the latest computer. You can use a five-year-old machine to run very heavy tasks that the newest tools in Natural Language Processing require,” she explains.

At the same time, the standardised setup makes teaching more seamless. All students work with the same standard configuration in UCloud, so any issues that arise are the same for everyone. This creates a shared sense of problem-solving, as challenges can be addressed collectively rather than handled individually by students on their own. As Mina puts it:

“Instead of stopping the lesson to solve individual problems, the problems become collective and an opportunity for learning for everyone. If we have a software issue – for example, a Python library version that is outdated or incompatible – it affects everyone, and we can solve it together.”

Preparing Students for Working Life

For Mina, using UCloud also helps prepare students for the reality that awaits them after graduation. According to her, many of the students who go on to IT positions will likely use cloud computing platforms rather than coding on local machines. In this way, the teaching becomes direct preparation for future job tasks and gives students experience with the technologies they will encounter in practice.

Advice for Other Instructors 

Mina has used UCloud since her bachelor’s degree and finds that the platform makes teaching both smoother and more engaging.

“I recommend that other instructors make use of the platform. You just have to get started – but feel free to ask colleagues for advice on how they use it. Get some inspiration, because UCloud is a fantastic tool. It can do a great many things, but like other systems, it can feel a bit overwhelming at first, so it’s a good idea to get some guidance along the way before you begin.”

Categories
Call Interactive HPC Research Supercomputing UCloud

H2-2026 National HPC Call is open

You can now apply for compute time on UCloud. DeiC has opened the first 2026 call for applications for access to Denmark’s national HPC facilities – and Interactive HPC – UCloud is part of this call.

So if your research needs extra compute resources on UCloud, now is the time to apply. These calls only open twice a year, so this is a great opportunity to consider applying in this round. Researchers (and PhD students) at Danish universities can apply.

Key dates

  • Call opens: 13 January 2026
  • Application deadline: 10 March 2026
  • Resources available from: 1 July 2026

Read more and apply via DeiC

Categories
Supercomputing Tutorial UCloud Webinars & Tutorials - video Workshop

Webinar Recording: Getting Started With UCloud

In this video tutorial you will watch a hands-on introduction to UCloud, the national research platform for compute, storage, and applications. The session is designed to help new users get started with UCloud and understand how to use the platform for research, teaching, and project work.

In the recording, we guide you through how to:

  • Log in to UCloud and navigate the dashboard
  • Understand key concepts such as projects, resources, and applications
  • Run your first job and apply for additional compute and storage resources
  • Manage files and collaborate using project workspaces
  • Explore the application catalogue and job submission options
  • Discover new features introduced in UCloud 4.0

This recording is relevant for students, researchers, and new UCloud users across all disciplines.

UCloud is beginner-friendly and does not require any technical background or prior experience with cloud computing.

Timestamps

00:00 – 02:20: Introduction 
What UCloud is, who it’s for, and what the webinar will cover.

02:20 – 03:50: Key terms you need to know
Simple explanations of essential concepts used throughout the platform.

03:50 – 04:30: Support resources and useful links
Where to find help on interactivehpc.dk and additional documentation.

04:30 – 06:10: Login process and UCloud dashboard overview
How to log in and navigate the main dashboard.

06:10 – 08:30: Running your first job
A quick walkthrough of launching an application on UCloud.

08:30 – 14:00: Applying for resources
How to request compute and storage resources for your project.

14:00 – 17:20: File system and Drives
How file storage works and how to manage your data.

17:20 – 18:00: Personal workspace vs project workspace
Key differences and when to use each.

18:00 – 21:30: Managing a UCloud project
Members, settings, allocations, and collaboration.

21:30 – 23:50: Resources page
Public and IP links, SSH keys, and related settings.

23:50 – 25:40: Application catalogue and documentation
How to find apps and access relevant guides.

25:40 – 28:50: Job submission page options
Configuring applications before starting a job.

28:50 – 29:50: Running job view
Monitoring jobs and understanding job status.

29:50 – 32:00: Work folder, output files, and Runs page
Where to find results, logs, and job history.

32:00 – 35:40: What’s new in UCloud 4.0
Command palette, file tree, Syncthing and usage page.

35:40 – 36:08: Conclusion and next steps
Summary and where to find further resources.