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High-performance computing at AAU
Explore the high-performance computing (HPC) resources available for AAU students and researchers, how they work and what they can be used for in your projects.
What is HPC?
High-performance computing (HPC) refers to the use of powerful computing resources to tackle complex and resource-intensive tasks that exceed the capabilities of standard computing systems. For researchers and students at AAU, HPC provides the necessary power to train machine learning models, run simulations, perform data analysis, and conduct modeling, among other tasks. This capability is invaluable across a wide range of academic disciplines.
Benefits from using HPC
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Parallel computing
AAU HPC provides access to specialized processors that enhance the speed and processing capabilities of the system, enabling the execution of highly parallelizable tasks.
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Fast data processing
HPC allows for much faster calculations than what your local machine can provide. Instead of reducing the data sets - reduce the processing time!
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Available at hand
Thanks to HPC, you can access your computing environment from anywhere using your laptop, allowing you to work independently.
Platform Overview
At AAU, researchers and students can access various HPC platforms to perform simulations, data analysis, and other resource-intensive tasks that would be impractical on standard computers.
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Strato
Built on a Linux-based system, Strato supports data-driven research that requires enhanced processing power with both CPU and GPU capabilities.
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UCloud
UCloud is a digital research platform developed by the SDU eScience Center, specifically designed to deliver high-performance computing with a strong emphasis on user experience.
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AI Cloud
AI Cloud is Aalborg University's primary GPU resource, tailored for machine learning and parallel processing tasks.
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AI-LAB
AI-LAB is designed exclusively for students at Aalborg University, offering high-performance computing (HPC) right at your fingertips.
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DeiC Throughput HPC
Through the Danish e-Infrastructure Cooperation (DeiC), CLAAUDIA can provide access to three National HPC facilities (Computerome 2.0, DTU Sophia, GenomeDK).
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LUMI
Through the Danish e-Infrastructure Cooperation (DeiC), CLAAUDIA can provide access to the pre-exascale LUMI supercomputer in Finland, with AMD based CPU and GPU resources available.
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EuroHPC
Aalborg University researchers are eligible to use the supercomputers of the EuroHPC.
Comparison table
Dive into the characteristics of the available HPC platforms
| Feature | Strato | UCloud | AI Cloud | AI-LAB |
|---|---|---|---|---|
| Available to researchers | - | |||
| Available to students | (CPU processing) | - | ||
| Sensitive data | - | - | - | |
| Ideal for | Model training, simulations | First-time users, data processing | Deep learning, large datasets | Student projects, deep learning |
| CPU processing | - | - | ||
| GPU processing | ||||
| Unlimitted GPU usage | - | - | ||
| Access interface | Terminal | Web browser | Terminal | Terminal |
| Possible to add GUI | - | - | ||
| Working interactively | - | - | ||
| Pre-installed apps | - | - | ||
| Recommended skills | Linux, SSH | None | Linux, Containerization | Linux, Containerization |
| Collaboration friendly |
HPC Decision Tree
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find the most suitable system for your project
Complete the HPC Decision Tree Quiz and find the most suitable HPC platform for your project. HPC Decision Tree is a tool which can assist you in exploring the HPC options fitting your specific needs by answering questions related to your project and research data.
