Category: Interactive HPC

Categories
Interactive HPC Teaching Tutorial Webinars & Tutorials - video

Webinar Recording: Transcribing and editing audio transcriptions with Transcriber and Speech Analyzer apps

In this video we will guide you through the complete pipeline of transcribing audio files from speech to text and editing and classifying transcription segments.

In this session, you’ll learn how to:

  • Use Transcriber for transcribing audio/video files. Transcriber is based on Open AI’s Whisper language model. The app can transcribe speech audio to text in various formats and uses the WhisperX package to perform speaker recognition.
  • Navigate the new, simple, drag and drop Transcriber user interface to make it easier for you to use AI to transcribe audio files.
  • Edit and classify the transcriptions with Speech Analyzer. Speech Analyzer is an application built on top of Label Studio, specifically optimized for dialogue analysis. It enables you to label, edit, and annotate transcriptions generated using Transcriber.
  • Perform a comprehensive dialogue analysis on UCloud involving transcribing audio files using Transcriber, followed by transcription analysis with Speech Analyzer.

All workflows will be executed inside a UCloud project environment with access to GPU resources.

Target audience: Researchers across all Departments, particularly Digital Humanities and Social Science, Students, AI interested.

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Interactive HPC Supercomputing Tutorial UCloud Webinars & Tutorials - video Workshop

Webinar recording: Fine-Tuning and Deploying  Large Language Models

In this video we will guide you through the complete pipeline of fine-tuning large language models (LLMs) for specialised tasks such as medical question-answering using NeMo Framework and Triton Inference Server.

  • Prepare and preprocess open-source datasets for fine-tuning.
  • Apply Parameter-Efficient Fine-Tuning (PEFT) using LoRA with NVIDIA NeMo Framework.
  • Deploy optimised LLMs using NVIDIA Triton Inference Server and TensorRT-LLM.
  • Generate a synthetic Q&A dataset using Label Studio connected to a live inference backend.
  • Fine-tune and evaluate your customised LLM for domain-specific applications.

All workflows will be executed inside a UCloud project environment with access to GPU resources.

Target audience: Machine learning practitioners, researchers, and engineers interested in LLM customisation, domain adaptation, or scalable model deployment.

Technical Level: Intermediate to Advanced.

Notebooks: https://github.com/emolinaro/ucloud-workshop-28-05-2025

Categories
Application Interactive HPC Supercomputing Teaching Tutorial Webinars & Tutorials - video

Webinar recording: UCloud courses hands-on

In this video we will go through the process of developing a course on UCloud, using UCloud Courses – a tool for hosting and managing university courses on UCloud. Want to know more about this new feature, check out our webinar recording introducing UCloud Courses.

Introduction

00:00 – Outline of the workshop agenda
03:10 – Introduction to the UCloud Courses concept
04:23 – Advantages of using UCloud Courses
05:56 – Outline of the steps involved in developing a UCloud Course
09:54 – Requesting and planning a UCloud Course
10:20 – Example of the planning and structuring of an existing UCloud Course

Developing a UCloud Course step by step

Setting up the environment
15:53 – Preliminary remarks
17:15 – Showing the existing UCloud Course that will be re-developed in the workshop
18:02 – Showing the UCloud-Courses GitHub repository
18:40 – Software requirements and -recommendations
20:22 – Short introduction to Git and GitHub
24:27 – Cloning the repository
25:15 – Creating a working branch
26:12 – What should go in the UCloud-Courses repository and what shouldn’t
27:24 – Installing the required dependencies

Creating a new UCloud Course and modifying the templates
28:00 – Creating a UCloud Course using a prepared script
30:31 – Walk-through of the different auto-generated files/folders in the course folder
33:35 – Short introduction to Docker
38:15 – Modifying the Dockerfile
42:32 – What should go in the UCloud-Courses repository and what shouldn’t
45:28 – Building the Docker image locally using a prepared script
47:54 – Modifying the starting script
01:00:50 – What can, shouldn’t, and mustn’t be changed while the course is running

Building and testing the course locally
01:05:00 – Re-building the Docker image locally using a prepared script
01:05:25 – Running a Docker container locally using a prepared script
01:10:58 – Opening the JupyterLab interface on localhost

Finalising the course app
01:12:48 – Opening a pull request and requesting code review
01:19:44 – Testing the course app on UCloud before it’s deployed

Closing remarks

01:25:44 – Reusing/updating an existing UCloud course
01:28:19 – The financial model in brief
01:29:38 – Useful links and resources

UCloud-Courses GitHub repository:
https://github.com/SDU-eScience/UCloud-Courses

README in the UCloud-Courses GitHub repository:
https://github.com/SDU-eScience/UCloud-Courses/blob/main/README.md

Wiki page in the UCloud-Courses GitHub repository:
https://github.com/SDU-eScience/UCloud-Courses/wiki

The UCloud course app redeveloped in the workshop (UCloud login required):
https://cloud.sdu.dk/app/jobs/create?app=nlp-demo-course_147222U005

eScience Servicedesk (point of first contact):
https://support.escience.sdu.dk/

Categories
Application Interactive HPC

New App: AlphaFold 3 – a game-changing tool for predicting protein structure

AlphaFold 3, the new AI model developed by Google DeepMind and Isomorphic Labs, can predict the structures of complexes formed by different biomolecules, including protein-DNA, protein-RNA, and protein-ligand interactions. 

AlphaFold 3 deployment on Interactive HPC – UCloud is optimized for use with GPUs, and includes the necessary multiple genetic (sequence) protein and RNA databases to run.

Beside the Batch Mode, additional app flavors (Lab Mode and Visualization Mode) allow respectively to use the software in a JupyterLab environment and to visualize protein structures obtained by running AlphaFold 3.

AlphaFold 3 has been implemented on Interactive HPC – UCloud to support specific type of work, e.g., accurate structure prediction and modelling, and is ready for use by all Interactive HPC – UCloud users.

For more details, visit the UCloud documentation for the app.

Categories
Call Interactive HPC Supercomputing

Reduced Resources in Upcoming national HPC Call

The position of Chair of the DeiC Board is currently vacant, leading to delays in decision-making processes and affecting upcoming national HPC calls.

John Renner Hansen has stepped down as Chair of the DeiC Board. As a result, the DeiC Board is currently unable to make financial decisions, which impacts several ongoing and upcoming HPC activities.

A new Chair is expected to be appointed by the Rectors’ Conference of Danish Universities in early August 2025.

Fewer Resources in Upcoming National HPC Call

The next national HPC call will open on 15 July 2025 and covers the compute period from 1 January to 31 December 2026. DeiC’s current contracts with DeiC Interactive HPC will expire on 31 December 2025, and work is underway to establish a new agreement. However, as the Board is not currently quorate, there is no guarantee that new agreements will be in place before the call opens. Therefore, the upcoming national call will only include national compute time on LUMI.

For more information, please contact your local Front Office.

This is an adaption of the story published by DeiC https://deic.dk/en/news/2025-6-20/delayed-quantum-calls-and

Categories
Application Interactive HPC Supercomputing

New App: Apache Kafka 

Users of DeiC Interactive HPC – UCloud can now access Apache Kafka, a high-performance event streaming platform designed for managing real-time data at scale. 

Kafka deployments on UCloud support multi-node configurations, enabling production-grade distributed logging, stream processing, data integration, and publish/subscribe messaging systems. 

Students and researchers can use Apache Kafka to collect, process, and analyse large volumes of real-time data – for example, streaming data from lab sensors, social media, or web clickstreams. It’s especially useful for building data pipelines in projects involving machine learning, IoT, or real-time analytics, enabling reproducible and scalable research workflows. 

For more details on the Apache Kafka application, visit UCloud docs for the full documentation.



Categories
Interactive HPC Supercomputing UCloud Workshop

Workshops on AI applications

Join us for three new and free online workshops to explore how these tools can transform your work. Discover AI Applications on DeiC Interactive HPC – UCloud

Workshop 1:

Transcribing and editing audio transcriptions with Transcriber and Speech Analyzer apps

Date: 22 May 2025

Time: 13:00 – 15:00 (CET)

Location: Online, via Zoom (link TBA)

Join us for a hands-on workshop where we guide you through the complete pipeline of transcribing audio files from speech to text and editing and classifying transcription segments.

In this session, you’ll learn how to:

  • Use Transcriber for transcribing audio/video files. Transcriber is based on Open AI’s Whisper language model. The app can transcribe speech audio to text in various formats and uses the WhisperX package to perform speaker recognition.
  • Navigate the new, simple, drag and drop Transcriber user interface to make it easier for you to use AI to transcribe audio files.
  • Edit and classify the transcriptions with Speech Analyzer. Speech Analyzer is an application built on top of Label Studio, specifically optimized for dialogue analysis. It enables you to label, edit, and annotate transcriptions generated using Transcriber.
  • Perform a comprehensive dialogue analysis on UCloud involving transcribing audio files using Transcriber, followed by transcription analysis with Speech Analyzer.

All workflows will be executed inside a UCloud project environment with access to GPU resources.

Target audience: Researchers across all Departments, particularly Digital Humanities and Social Science, Students, AI interested.

Technical Level: Basic to Intermediate.

Sign up for this workshop

Workshop 2:

ChatUI and CVAT pipelines

Date: 27 May 2025

Time: 13:00 – 15:00 (CET)

Location: Online, via Zoom (link TBA)

Join us for a hands-on workshop where we guide you through two different AI based workflows, involving ChatUI and CVAT apps.

In this session, you’ll learn how to:

  • Use Chat UI as a flexible interface for hosting of various LLM models, and interact via a chat or API environment.
  • Use ChatUI for semantic search in a knowledge base.
  • Use CVAT as a powerful annotation tool, including image classification, object detection, semantic and instance segmentation, and video / 3D annotations.
  • Use advanced CVAT features including auto-annotation, algorithmic assistance, management and analytics.

All workflows will be executed inside a UCloud project environment with access to GPU resources.

Target audience: Researchers across all fields, particularly transport, robotics, digital humanities, social sciences, machine learning and students.

Technical Level: Basic to Intermediate.

Sign up for this workshop

Workshop 3:

Fine-Tuning and Deploying  Large Language Models with NeMo Framework and Triton Inference Server

Date: 28 May 2025

Time: 13:00 – 15:00 (CET)

Location: Online, via Zoom (link TBA)

Join us for a hands-on workshop where we guide you through the complete pipeline of fine-tuning large language models (LLMs) for specialized tasks such as medical question-answering!

In this session, you’ll learn how to:

  • Prepare and preprocess open-source datasets for fine-tuning.
  • Apply Parameter-Efficient Fine-Tuning (PEFT) using LoRA with NVIDIA NeMo Framework.
  • Deploy optimized LLMs using NVIDIA Triton Inference Server and TensorRT-LLM.
  • Generate a synthetic Q&A dataset using Label Studio connected to a live inference backend.
  • Fine-tune and evaluate your customized LLM for domain-specific applications.

All workflows will be executed inside a UCloud project environment with access to GPU resources.

Target audience: Machine learning practitioners, researchers, and engineers interested in LLM customization, domain adaptation, or scalable model deployment.

Technical Level: Intermediate to Advanced.

Sign up for this workshop

DeiC Interactive HPC provides researchers at Danish universities with access to a variety of AI applications on UCloud that enable them to accelerate their research through powerful and secure computational tools.

Through online workshops the DeiC Interactive HPC Consortium will introduce both new and experienced users to DeiC Interactive HPC/UCloud’s AI app portfolio.

The sessions are designed to equip researchers and students with the knowledge and skills needed to effectively harness DeiC Interactive HPC/UCloud’s AI tools for their research.

Feel free to share with colleagues and peers who might benefit. See you there!

Categories
Interactive HPC Supercomputing UCloud

DeiC Interactive HPC now has 15,000 Users

The DeiC Interactive HPC consortium is thrilled to announce that the service, powered by the UCloud software, has reached another significant milestone: 15,000 users. This achievement underscores the service’s growing popularity and its pivotal role in advancing digital research through user-friendly supercomputing access.

Since its inception, DeiC Interactive HPC has been dedicated to providing researchers with seamless access to high-performance computing (HPC) resources. The service’s intuitive interface and capabilities have revolutionized the way researchers approach complex computational tasks, making HPC accessible to a broader audience.

DeiC Interactive HPC’s success is a testament to the collaborative efforts of the consortium that operates the service. Together, we have created an environment where researchers from diverse fields can leverage cutting-edge technology to drive innovation and discovery.

As DeiC Interactive HPC and UCloud continues to grow, we remain committed to enhancing the service’s features and expanding its reach. The goal is to empower even more researchers with the tools they need to tackle some of the most pressing scientific challenges of our time.

Categories
Interactive HPC Research UCloud Use case

DeiC Interactive HPC Crucial for Danish AI Language Models

By Jasper Riis-Hansen and Line Ejby Sørensen, Center for Humanities Computing (CHC), Aarhus University

DeiC Interactive HPC – UCloud plays a central role in the Danish Foundation Models (DFM) project, which forms part of the Danish government’s strategic initiative for artificial intelligence.

Danish Foundation Models (DFM) is supported by the Ministry of Digital Affairs as part of the national AI strategy, which aims to ensure that Denmark has access to advanced and tailored language models. These models are intended for use across a wide range of sectors, including healthcare, public administration, education, and private enterprise.

A shared digital environment

The DFM project brings together Danish universities, research institutions, and industry partners in a joint effort to establish new standards for ethically responsible and inclusive AI language technologies.

The project is a collaboration between Aarhus University, the University of Copenhagen, the University of Southern Denmark, and the Alexandra Institute. DeiC Interactive HPC – UCloud plays a vital role in this work by providing high data security, scalable computing power, and, not least, an accessible, secure, national cloud platform that enables collaboration among project partners.

“UCloud forms the foundation for an important step in research digitalisation, as the platform provides easy access to computing power, enabling scalable data analysis and modelling, while also offering a secure environment for handling sensitive data. The platform also facilitates collaboration across institutions and allows us to manage data access as needed. This is particularly relevant in the DFM project, which includes many partners participating at different levels.”
Postdoc Kenneth Enevoldsen

Data security and computing power

Because AI models are often trained on sensitive data, it is crucial that data processing complies with both GDPR and Danish security standards. UCloud is ISO27001-certified and specifically designed to meet both Danish and EU requirements for secure data handling.

“In the DFM project, we work with very large amounts of data from a variety of sources – including sensitive data that the models are trained on – and this places high demands on data security. That is why UCloud is such a valuable tool for the project – precisely because of its high level of data security and access to scalable computing power.”
Postdoc Kenneth Enevoldsen

Although DFM also makes use of European supercomputers such as LUMI in Finland and Leonardo in Italy, the day-to-day operations of the project are heavily reliant on UCloud. In addition to being a springboard for high-performance computing, UCloud also provides a secure and user-friendly platform with a wide range of accessible applications – all essential for daily research, collaboration, data processing, and innovation across the project’s interdisciplinary team.

Critical infrastructure for Danish AI development

DFM’s principal investigators, Kristoffer Nielbo and Peter Schneider-Kamp, emphasise that the robust digital research environment provided by DeiC Interactive HPC – UCloud constitutes critical infrastructure. It streamlines workflows, enhances collaboration, and accelerates the development of both language and AI technologies.

“Without UCloud, the DFM project would have had to develop this type of digital infrastructure itself – with significant time and financial costs. The platform’s role in the project clearly demonstrates how robust, collaborative digital research environments are essential to Denmark’s AI strategies.”

FACTS: Danish Foundation Models (DFM)

Danish Foundation Models (DFM) is a collaborative project involving Aarhus University, the University of Copenhagen, the University of Southern Denmark, and the Alexandra Institute.

The project is supported by the Ministry of Digital Affairs with a grant of DKK 30.7 million and aims to develop advanced language models with open access and transparent development processes.

The models are specifically tailored to Danish and other Scandinavian languages and cultures and are intended for use across sectors such as healthcare, public administration, education, and business.

DFM seeks to establish a new standard for ethically responsible, inclusive, and transparent AI language technology – for the benefit of both Danish society and the research community.

For more information, visit: Danish Foundation Models, Ministry of Digital Affairs press release

Categories
Interactive HPC Research Supercomputing UCloud

DeiC Interactive HPC Revolutionises Interdisciplinary Research with User-Friendly Supercomputing Access

With 10,000 users, DeiC Interactive HPC has established itself as one of Europe’s most popular HPC facilities, thanks to an unprecedented democratisation of access to advanced computing resources. These resources, once reserved for specialised research fields and technically adept specialists, are now accessible to any researcher with a dataset and a vision.

Through a newly developed, simple, and graphical user interface, DeiC Interactive HPC, also known as UCloud, makes it easier than ever to gain interactive access to supercomputing. This approach reduces technical barriers and enhances research collaboration by offering shared, easily accessible virtual environments. As a result, DeiC Interactive HPC supports dynamic and interdisciplinary research, accelerating research processes and promoting innovation in fields ranging from bioinformatics to digital humanities.

Democratising Access to HPC

The trend towards more interactive use of technology, including HPC, reflects efforts to make the STEM field more inclusive and accessible, mirroring broader societal changes towards diversity and inclusion in technology and science. DeiC Interactive HPC’s user-friendly approach has attracted a broad spectrum of users, including those from nearly all Danish universities and individuals with varying levels of technical expertise, notably many students.

“We are proud to highlight the growing diversity among DeiC Interactive HPC users, a development that further distinguishes DeiC Interactive HPC from traditional HPC systems. We see continuous growth in user numbers and are now celebrating surpassing 10,000 users across a very broad spectrum of research disciplines, which is impressive in the HPC field. Of these users, 50% are students, reflecting DeiC Interactive HPC’s success in attracting new users and serving as a bridge to larger European HPC facilities,” says Professor Kristoffer Nielbo, representing Aarhus University in the DeiC Interactive HPC Consortium.

Research Areas
Students

By simplifying access to supercomputers, DeiC Interactive HPC democratises powerful data processing resources, enabling a wider range of researchers and academics to conduct innovative research without the steep learning curve traditionally associated with HPC. This inclusivity fosters scientific collaboration and creativity, enriching the HPC community with a diversity of perspectives and ideas.

“We continuously work to improve DeiC Interactive HPC with a democratic approach, using user feedback to ensure our focus is in the right place. This is also reflected in our new update – UCloud version 2 – which aims to increase efficiency and improve the user experience for researchers. It is part of our DNA as an interactive HPC facility to always keep the user in mind and develop apps and user interfaces based on user needs. Therefore, we encourage our users to reach out to us with their wishes and ideas,” says Professor Claudio Pica, representing the University of Southern Denmark in the DeiC Interactive HPC Consortium.

Did You Know

– that DeiC Interactive HPC provides resources for developing large AI language models through initiatives such as Danish Foundation Models (DFM) and the new Danish Language Model Consortium?

– that nearly 80 apps are available via UCloud’s App Store, including the Chat-GPT-like app, Chat-UI, and transcription tools Transcriber and Whisper Transcription?

– that 25% of users on Interactive HPC come from the Social Sciences & Humanities, a unique figure as HPC traditionally caters almost exclusively to Natural Science, Health/Life Science, and Engineering?

An All Danish and Highly Secure System

Despite its internationally sounding name, UCloud, DeiC Interactive HPC is part of the Danish HPC landscape, funded by Danish universities and the Ministry of Education and Research. The increased focus on developing a new generation of highly user-friendly applications means that researchers and other university staff can now use intuitive applications for transcribing sensitive data via DeiC Interactive HPC.

“DeiC Interactive HPC has already developed applications based on the same transcription technology found online and made them available in a secure environment through the UCloud platform. These transcription applications are just the beginning of a series of targeted secure applications that do not require prior experience, and we are always open to user input and ideas that arise from their unique needs but often prove beneficial to many,” says Lars Sørensen, Head of Digitalisation, representing Aalborg University and CLAAUDIA in the DeiC Interactive HPC Consortium.

By making advanced data processing more accessible to researchers from various disciplines, DeiC Interactive HPC helps break down the technical barriers that previously limited access to these resources. With an increasing number of students and new users from diverse backgrounds combined with continuous engagement in user-centred innovation, DeiC Interactive HPC not only supports the academic community but also plays a crucial role in promoting a more inclusive and productive research environment.

New users
Universities

For further information and high resolution graphics, contact:
Kristoffer Nielbo, Director of Center for Humanities Computing, Aarhus University, 26832608 kln@cas.au.dk

About DeiC Interactive HPC (UCloud)

UCloud offers access to advanced tools such as quantum simulation apps and H100 GPUs as well as applications aimed at data analysis and visualisation.

In data analysis, Python and Jupyter notebooks are particularly prominent, catering to the interactive, ad hoc, and data-centric workflows common in the field. These tools are highly valued for their user-friendliness in handling rapidly changing software environments and offer rich user interfaces, a significant advantage compared to traditional HPC setups, which can be more complex or less flexible.

Furthermore, the integration of tools such as Conda for managing software packages, Jupyter notebooks, Rstudio, Coder, and Dask for parallel computing significantly enhances the usability of HPC resources for interactive and on-demand data processing needs. These tools help bridge the gap between the hardware of complex HPC systems and the user-friendly software environments that data scientists require.

Links

About DeiC Interactive HPC

Use Cases and News

News About the New UI

About the Consortium

DeiC Interactive HPC (UCloud) is a successful collaboration between three universities: SDU, AU, and AAU.

Aalborg University, CLAAUDIA, represented by Lars Sørensen

SDU, eScience Center, represented by Professor Claudio Pica

Aarhus University, Center for Humanities Computing, represented by Professor Kristoffer Nielbo