Are you using HPC and AI to tackle the world’s most urgent challenges?
Join HiDALGO2 at the 16th International Conference on Parallel Processing and Applied Mathematics (#PPAM2026) in Poznań, Poland.
We are officially inviting submissions for our workshop: Advancements of Global Challenges Applications (AGCA).
Call for Papers: 2nd AGCA Workshop at PPAM 2026 – Tackling Global Challenges with HPC Read More »
A new publication by HiDALGO2 researchers focuses on improving the efficiency of machine learning (ML) workloads in High-Performance Computing (HPC) environments.
HiDALGO2 Researchers Publish New Paper on Multi-GPU Machine Learning Optimization Read More »
HiDALGO2 is delighted to announce that three researchers with the project have been invited to guest edit a special issue of the prestigious journal Electronics. Project Coordinator Dr Marcin Lawenda (Poznan Supercomputing and Networking Center), Dr Harald Köstler (Friedrich-Alexander-University) and Prof. Christophe Prud’homme (University of Strasbourg) will oversee the publication of the special issue under
HiDALGO2 Researchers to Edit Special Issue of Journal “Electronics” Read More »
An advanced deep learning surrogate model trained on CFD data achieves high-fidelity fluid dynamics predictions at a fraction of the computational cost, accelerating simulation workflows.
An Advanced Surrogate Model Approach for Enhancing Fluid Dynamics Simulations Read More »
During the 3-day training, you will learn how to create containers for HiDALGO2 codes and scientific HPC applications and implement CI/CD workflows using GitHub Actions, GitLab Runners, and JacamarCI.
Training Session: Containerization, CI/CD, and Benchmarking Solutions for HPC Read More »
In what may prove to be a significant milestone in High Performance Computing (HPC), researchers with HiDALGO2 have demonstrated the potential of a new code called Xyst to run efficiently on almost 200,000 CPU cores in parallel. While further validation is necessary, early results are promising and indicate that Xyst may allow certain complex modelling
