Workshop & hackathon: Exascale women on stage!
V dňoch 12. – 14. júna na pôde Humboldtovej univerzity v Berlíne bude prebiehať workshop a hackathon Exascale women on stage! This event is organized by women for women to learn about each others' research and build professional networks. The event is open to all female scientists at all professional levels – including master students, PhD students, postdocs, and professors – working on the development of methods and codes to bring electronic-structure theory to the exascale.The workshop is organized by the NOMAD CoE.
The event serves two purposes:
- First, the scientists will discuss their research and share experiences.
- Second, they will gather ideas and develop a joint strategy on how to attract more female colleagues to the field. In a hackathon style, they will develop materials for their needs.
Urban buildings awaken: Slovak AI gives a second chance to underused spaces 4 Mar - Mestá sú živé organizmy, ktoré sa neustále menia. Mnohí z nás však v susedstve denne míňajú tiché svedectvá minulosti – prázdne školy, nevyužívané úrady či chátrajúce verejné budovy. Často si kladieme otázky: „Prečo je to zatvorené?“ „Nemohol by tu byť radšej denný stacionár, škôlka alebo kultúrne centrum?“
BeeGFS in Practice — Parallel File Systems for HPC, AI and Data-Intensive Workloads 6 Feb - This webinar introduces BeeGFS, a leading parallel file system designed to support demanding HPC, AI, and data-intensive workloads. Experts from ThinkParQ will explain how parallel file systems work, how BeeGFS is architected, and how it is used in practice across academic, research, and industrial environments.
When a production line knows what will happen in 10 minutes 5 Feb - Every disruption on a production line creates stress. Machines stop, people wait, production slows down, and decisions must be made under pressure. In the food industry—especially in the production of filled pasta products, where the process follows a strictly sequential set of technological steps—one unexpected issue at the end of the line can bring the entire production flow to a halt. But what if the production line could warn in advance that a problem will occur in a few minutes? Or help decide, already during a shift, whether it still makes sense to plan packaging later the same day? These were exactly the questions that stood at the beginning of a research collaboration that brought together industrial data, artificial intelligence, and supercomputing power.