🎓 NHR Conference '25

The aim of the NHR conferences is to bring together HPC users working on selected topics, varying each year. Users of the NHR Centers will have the opportunity to present their projects in a poster session or contributed talk, and to exchange ideas with the consulting and operational teams of the NHR-Centers. 

For next year's conference at Georg-August-Universität Göttingen, the topics are: 

• AI in Social Sciences 
• Life Sciences
• Data Management & Storage

Registration:  https://indico.kit.edu/event/4836/

For this year's conference at NHR@Göttingen, the topics are:

• AI in Social Sciences:

Social sciences are increasingly adopting AI and HPC to analyze societal dynamics in greater depth. Today, researchers employ detailed simulations, natural language processing, and agent-based models to explore phenomena ranging from public sentiment to electoral dynamics. These techniques streamline the analysis of extensive datasets and enable detailed simulations that uncover subtle patterns and spark fresh research. 

This section brings together researchers working at the intersection of AI, HPC, and the social sciences. Alongside technical and methodological advances, we will also explore critical challenges and open up new ways of tracing social phenomena. We invite contributions that explore such new avenues. 

• Life Sciences

As the life sciences are moving rapidly from a descriptive discipline to a predictive one, researchers have to integrate vast amounts of heterogeneous data and develop highly nonlinear, multi-scale models. Data sources in the life sciences are diverse and include genome and proteome sequences, metabolic data, microscopy images and videos, timeseries, as well as clinical records and medical imagery. Interpreting nonlinear data in high-dimensional spaces is challenging for the human brain.

Distilling physical laws or mathematical models from the data therefore requires scalable computational statistics and machine learning approaches. This entire workflow from handling and fusing data to developing and training models requires innovative HPC approaches to ensure scalability, flexibility, performance while maintaining fast development cycles. Abstract submissions for talks or posters covering this research field are welcome.

• Data Management & Storage

Efficient data management and storage are crucial for HPC applications and systems to ensure seamless access, processing, and analysis of vast datasets while optimizing performance and resource utilization. Scalable storage solutions, parallel file systems, and data lifecycle management are key to handling large-scale simulations, AI workloads and the integration of analysis pipelines from large-scale research infrastructures and experiments.

We invite talks and posters on innovative storage architectures, data-intensive workflows, optimization strategies, FAIR data principles, and best practices in HPC data management. Contributions on real-world applications, emerging storage technologies, and interdisciplinary collaborations are highly encouraged to foster knowledge exchange and innovation in HPC.

During the Workshop and Networking Days (September 24-25) NHR members and their guests will provide a range of workshops and networking meetings that are partly open for external participants, please check the final program (expected in July 2025) for more details.