SRI DiTEnS is developing methods for discursive transformation in local energy systems, using urban digital twins involving virtual reality to support decision making among stakeholders.
The HiDALGO2 project is addressing challenges caused by climate change, focusing on technical issues related to scalability on HPC and AI infrastructures, the use of computational fluid dynamics methods, and uncertainty analysis.
The SEQUOIA End-to-End project aims to develop transparent, automated, and controllable end-to-end solutions for the industrial use of hybrid quantum applications and algorithms through holistic quantum software engineering.
DECICE is developing an open and portable cloud management framework that will enable the automatic and adaptive optimization of software applications for heterogeneous computing architectures.
Focusing on a large-scale, high-resolution earth system model, TOPIO is investigating read and write rates for large amounts of data on high-performance file systems, as well as approaches that use compression to reduce the amount of data without causing a significant loss of information.
The 3xa project will develop scalable methods for the simulation of three-body interactions in particle systems, applying vectorized kernels, dynamic load balancing approaches and adaptive resolution schemata.
This project’s goal is to increase the accuracy and reduce the uncertainty of performance and load assessment tools and associated procedures that are commonly used in the industrial design and certification of modern wind energy systems.
In the first ever project to connect computers in wind parks with an HPC center, WindHPC aims to reduce energy consumption by improving efficiency in simulation codes, HPC workflows, and data management.
targetDART is developing a task-based approach for highly scalable simulation software that mitigates load-imbalance on heterogenous systems through dynamic, adaptive and reactive distribution of computational load across compute resources.
EE-HPC is testing an approach for improving energy efficiency in HPC systems by automatically regulating system parameters and settings based on current job requirements.
The goal of Gaia-X4ICM is to implement a scaling production platform based on the Gaia-X ecosystem for the InnovationCampus Mobility of the Future (ICM) to make Gaia-X more usable for production of planning systems, industrial controls, and sensor data, among other applications.
