10th International Conference on Polymer Materials in the Automotive Industry – PMA 2025 and the 26th Slovak Rubber Conference
The prestigious scientific conference PMA & SRC 2025, focused on polymer materials in the automotive industry and rubber research, was held at Smolenice Castle from May 21 to 23, 2025. Among the speakers was Lucia Malíčková from the National Supercomputing Centre (NSCC Slovakia) and the National Competence Centre for High-Performance Computing (NCC for HPC).
In her presentation titled “Computational Modelling and High Performance Computing Driven Innovation in the Development of Polymeric Materials in the Context of the European Competence Centre Framework”, she introduced the potential of high-performance computing (HPC) in the modelling and development of innovative polymeric materials. She also emphasized the importance of collaboration within the European network of competence centres for HPC.
Participation in the event strengthened the connection between the industrial and academic sectors and highlighted the growing importance of HPC solutions for sustainable materials development in the context of the circular economy and innovations in the automotive sector.
The conference proceedings, which also include the contribution by Lucia Malíčková..
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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.