The SC22 Conference – the world’s leading HPC event – will take place from November 13-18, 2022 in Dallas, Texas, USA. After two years of remote participation, the High-Performance Computing Center Stuttgart (HLRS) will finally be back onsite at the conference. We look forward to seeing you there.
Visit us in booth 1226 to meet HLRS staff and learn all about our recent activities. Representatives of our visualization department will present recent research using digital twins for city planning, including a virtual reality application that integrates a wheelchair to support mobility planning for disabled people. Information will also be available about the EuroCC project, which is coordinating the expansion of HPC competencies across Europe.
Click here to visit the SC22 website and register.
Our staff will also be contributing to the conference program, as indicated below:
Kay Bailey Hutchison Convention Center Dallas 650 S. Griffin St., Dallas, TX, 75202
13. Nov 2022
18. Nov 2022
Dallas
Englisch
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Tuesday, 15 November 2022 5pm - 6:45pm CST Location: D167 More Information
Since 2018 the Partnership for Advanced Computing in Europe (PRACE) has engaged in the coordination of European HPC activities, including access to HPC systems, user support, training, policy, technology, operations, and dissemination. The initiative led to the development of the "HPC in Europe" portal, an online mechanism to structure and present European HPC services.
Since then, the European HPC strategy has undergone significant changes, particularly with the launch of the EuroHPC Joint Undertaking and other new coordination activities. The objective of this Birds-of-a-Feather Session is to present the current status of the European HPC ecosystem, discuss further exploitation of the HPC portal, and consider experiences in the CASTIEL/EuroCC network, which is helping to build HPC expertise across Europe by fostering collaboration among 33 national European Competence Centres.
Tuesday, 15 November 2022 8:30am - 5pm CST Location: C1-2-3 More Information
Appropriately adjusting the power draw of computational hardware plays a crucial role in its efficient use. While vendors have already implemented hardware-controlled power management, additional energy savings are available, depending on the state of the machine. We propose the online classification of such states based on computationally informed machine learning algorithms to adjust the power cap of the next time step. This research highlights that the overall energy consumption can be reduced significantly, often without a prohibitive penalty in the runtime of the applications.
This research poster by Johannes Gebert from HLRS will be presented on 15 November, and will remain on display in the poster area on November 15-17.
