
Projects
Hessian scientists of various disciplines are using High Performance Computers for their research.
Hessian scientists of various disciplines are using High Performance Computers for their research.
Displaying 61 - 90 of 139
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...
The exaFOAM project (https://exafoam.eu) aims at overcoming the current limitations of Computational Fluid Dynamics (CFD ...
In variational inference, we want to approximate an intractable target distribution (often given as a posterior ...
Recent developments in the field of complex systems have shown that real-world multiagent systems are often not ...
In previous project we investigated on the scaling and the load balancing of the Ice-sheet and Sea-level System Model ...
Earth modeling is a wide field of different scientific domains, e.g., ice-modeling. All domains have in common, that ...
In the context of earth system modeling the simulation of ice-sheets is an important aspect. Ice-sheet modeling contains ...
Typical HPC applications represent simulations of large scientific problems. Usually, these applications alternate ...
The current project aims to reveal the relevant intrinsic mechanisms responsible for the coupling of the lattice and ...
NV centers – a nitrogen atom together with a vacancy – embedded in diamond provide a promising system to generate ...
The Software-Factory 4.0 (SF4.0) is a 4-year LOEWE1 project funded by the German State of Hesse and involves several ...
The message passing interface (MPI) is the de-facto standard for distributed high performance computing. However, it ...
Within the last decade, deep neural networks have attracted much attention from academia and industry. Such a wide ...
Trajectory optimization and model predictive control are essential techniques underpinning advanced robotic applications ...
Genetic Algorithms (GAs) are a popular heuristic optimization method inspired by biological evolution. We implemented a ...
Ideal one-dimensional (1D) electronic systems are fascinating, as they show quantisation of conductance, charge-density ...
Antiferroelectric (AFE) materials have recently been of a great interest, due to their unique applications in the energy ...
The electronic structure plays a key role in determining the physical properties of highly correlated electron systems ...
Reinforcement Learning is a powerful approach to achieve optimal behaviour. However, it typically requires a manual ...
Modeling interaction dynamics to generate robot trajectories that enable a robot to adapt and react to a human’s actions ...
Reinforcement learning methods for robotics are increasingly successful due to the constant development of better policy ...
DNA-PKcs is a gateway protein of the Non-Homologous End Joining DNA Repair Pathway. Which is the process of repairing ...
Empirical performance modeling is a proven instrument to analyze the scaling behavior of HPC applications. Using a set ...
One important aim of modern energy-conserving technologies is magnetic cooling at room temperature. This environmentally ...
This project is concerned with promoting a more efficient usage of the HPC Systems. The two major technologies used to ...
Model-based value expansion methods promise to improve the quality of value function targets and, thereby, the ...
The field of spintronics recently gained much interest because it promises faster, smaller and less energy consuming ...
Femtosecond laser pulses excite the electrons of matter to a high temperature whereas the ions remain mainly unaffected ...
Reinforcement Learning (RL) has proven to be an empirically very successful approach to solving sequential decision ...
The Nonparametric Off-Policy Policy Gradient (NOPG) is a policy gradient algorithm to solve reinforcement learning tasks ...