Artificial Intelligence & Data Analytics

Image f. Artificial Intelligence & Data Analytics

Artificial intelligence, machine learning, deep learning, and high-performance data analytics have opened new opportunities across many domains. At HLRS, we support such innovation both by providing access to powerful systems for data analysis and helping our system users to make the most of them.

Application areas

We not only provide AI solutions for researchers in science and engineering but also work with individuals and organizations interested in testing new applications of AI technologies in other fields. In the past, this has meant enabling research in fields like computational fluid dynamics and materials science as well as supporting non-scientific domains including business and finance, digital media, literary studies, and the visual and performing arts.

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Systems for AI & data analytics

HLRS maintains multiple computing systems containing graphic processing units (GPUs), which provide the necessary speed and architecture for high-performance data analysis and artificial intelligence applications.

HPE Apollo (Hawk)

HLRS's flagship supercomputer enables large-scale data analytics as well as new kinds of hybrid workflows that combine HPC and AI.

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Cray CS Storm

Based on a GPU architecture, the CS-Storm is optimized for AI workloads and processing-intensive applications for machine learning and deep learning.

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AMD GPU System

Integrated into our Vulcan cluster, this system is dedicated to research related to the COVID-19 pandemic and other needs for crisis computing.

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Hybrid workflows combine HPC & AI

HLRS is preparing for the future of high-performance computing, which will combine HPC and AI in ways that enable a more seamless, iterative process of data generation and analysis.

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Are you interested in developing skills for data analytics on high-performance computing systems? We regularly offer courses in machine learning and deep learning that can help you turn your ideas into AI solutions.

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HLRS systems accommodate the latest versions of frequently used programming languages for machine learning and AI, including Apache Spark, TensorFlow, and PyTorch. HLRS also makes it possible for users to port their own software to our systems using PIP (Python), Anaconda, and container frameworks.

Featured projects

In addition to providing hardware and solutions for AI, research scientists at HLRS coordinate and contribute to collaborative, funded research projects that are addressing key technical problems facing the AI field and exploring potential applications of AI to solve pressing challenges. These activities enable us to build expertise and help us to better address the interests and needs of our system users.


The HiDALGO2 project is addressing challenges caused by climate change, focusing on technical issues related to scalability on HPC and AI infrastructures, the use of computational fluid dynamics methods, and uncertainty analysis.

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HLRS is the coordinating center for this project to integrate artificial intelligence (AI) topics into curricula at the University of Stuttgart, and to implement AI technologies to improve instruction.

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DECICE is developing an open and portable cloud management framework that will enable the automatic and adaptive optimization of software applications for heterogeneous computing architectures.

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Ethical aspects of artificial intelligence

Philosophers and social scientists at HLRS are engaged in research to better understand and address the ethical problems that can arise when AI algorithms are used in decision making.

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