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.
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.
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.
HLRS's flagship supercomputer enables large-scale data analytics as well as new kinds of hybrid workflows that combine HPC and AI.
Based on a GPU architecture, the CS-Storm is optimized for AI workloads and processing-intensive applications for machine learning and deep learning.
Integrated into our Vulcan cluster, this system is dedicated to research related to the COVID-19 pandemic and other needs for crisis computing.
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.
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.
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.
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.
This project is researching methods for analyzing large datasets produced by modeling and simulation, with the goal of implementing a framework that combines HPC and data analytics.
CYBELE is integrating tools from high-performance computing, high-performance data analytics, and cloud computing to support the development of more productive, data driven methods for increasing agricultural productivity and reducing food scarcity.
This project is developing novel methods, algorithms, and software for HPC and HPDA to model and simulate complex processes that arise in connection with major global challenges.
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.
Head, Service Management and Business Processes
Sep 20, 2021
Jul 29, 2021
May 11, 2021
Apr 19, 2021
High-Performance Computing Center Stuttgart
Nobelstraße 19, 70569 Stuttgart, Germany
+49 (0) 711 / 685-87 209
A member of the Gauss Centre for Supercomputing, HLRS is one of three German national centers for high-performance computing.
HLRS is a central unit of the University of Stuttgart.