Insights from the Austrian-Slovenian HPC Meeting 2024

The Austrian-Slovenian HPC Meeting (ASHPC24) took place from June 10 13, 2024, in Grundlsee, Austria. This annual gathering has become a cornerstone for scientists and technicians in the high-performance computing (HPC) community, providing a platform to discuss the latest advancements and applications in HPC technology.

EXCELLERAT P2 shines at ISC High Performance 2024

From 12-16 May in Hamburg, ISC High Performance 2024 brought together more than 3,000 attendees from 51 countries, focusing on HPC, AI, and Quantum Computing. Highlights included Sophia Honisch (HLRS) introducing EXCELLERAT P2, showcasing HPC solutions for engineering challenges, and Dennis Grieger (HLRS) presenting advancements in in-situ visualization at WOIV’24.

Transforming Engineering with Artificial Intelligence and High-Performance Computing

In today’s rapidly evolving research and engineering landscape, the convergence of artificial intelligence (AI) and high-performance computing (HPC) has become a transformative force. The synergy of AI and HPC is reshaping industries such as manufacturing, automotive, energy, aerospace, and climate research. From designing smarter vehicles to enabling sustainable energy sources and improving aerospace precision, AI and HPC are making engineering smarter, safer, and more sustainable. In this blog post, we will provide some insight on applications of AI and HPC in some engineering sectors including our own EXCELLERAT approaches.

HPC for Industry: an overview of the European landscape

Industry holds a vital position within the economic framework of the European Union, contributing significantly to its prosperity and progress. The following blog article provides an overview of the pivotal role of HPC in enhancing the competitiveness of industry, especially SMEs, across sectors.

EXCELLERAT Partners at SC23: Nominations, Collaborations, and Cutting-Edge HPC

From November 12 to 17, 2023, the high-performance computing (HPC) world converged at the International Conference for High-Performance Computing, Networking, Storage, and Analysis – SC23 and EXCELLERAT was no exception. With a record over 14,000 attendees and 438 exhibitors, SC23 lived up to its reputation as the premier event for scientists, engineers, researchers, educators, programmers, and developers in the HPC community.
While EXCELLERAT didn’t have a physical booth of its own, its activities were well-represented by project partners: BSC, HLRS, and SiPearl were exhibitors, and KTH was involved in the technical programme.

EXCELLERAT CoE presented at the Day of the Slovenian Supercomputer Network

On Thursday, November 16, 2023, the “Day of the Slovenian Supercomputer Network” was organized by the National Competence Center SLING in Ljubljana, Slovenia. One of the biggest HPC events in Slovenia gathered visitors from the entire HPC value chain.

The varied program included presentations on the activities of the National Competence Center (NCC) and Centers of Excellence (CoEs). Furthermore, examples of the effective use of powerful supercomputers in industry and academia were presented by research institutions and companies, and the possibilities of accessing HPC infrastructure were explained.


EXCELLERAT P2 was successfully represented at the 17th International Symposium on Operations Research in Slovenia – SOR’23, held in Bled, Slovenia, September 20-22, 2023.

Removing the warm up period from the output of a time-dependent simulation

A simulation software often computes a configuration in a step response fashion. Indeed, it starts from an approximate initial state and iteratively advances towards a statistically converged state that satisfies the physical constraints of the model. In Computational Fluid Dynamics (CFD), for instance, the conservation laws are progressively enforced, resulting in global signals with similar characteristics. Consequently, before reaching a statistically steady state, there is a warm-up period unsatisfactory from the modeling point of view, that should be discarded in our data collection.