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License: CC BY ND
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Conference object . 2025
License: CC BY ND
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HPC and AI in Germany | Resources and Support

Authors: Hermanns, Marc-André; Lauscher, Katharina; Justin, Lausberg; Landesgeschäftsstelle HPC.NRW;

HPC and AI in Germany | Resources and Support

Abstract

Researchers from a broad spectrum of scientific fields use computers to aid their research, often starting at their own laptop or institutional workstation. At some point in the research, additional help in form of algorithmic or software engineering consultancy or even additional computational resources in form of access to high-performance computing (HPC) systems may become necessary. Furthermore, on the side of AI, it may be unclear how practices of machine learning and artificial intelligence could be employed for their specific research. This poster aims at enabling researchers to identify resources for computing time, application support and training on topics of HPC and AI, by presenting a collection of contacts and further information on initiatives in Germany to aid them in their work. It ties together resources, both on the state level, with information on HPC competence networks, as well as the national level, with information on the NHR initiative (Nationales Hochleistungs-Rechnen), the National AI Service Centers, as well as national resources of the Helmholtz Association. As such, it enables participants at the conference, as well as anyone viewing the poster later, to identify quickly contacts close to their institution or domain to receive assistance with HPC and AI services.

Related Organizations
Keywords

AI, HPC, Computing Resources, Training, User Support

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green