NHR4CES@RWTH
Rheinisch-Westfälische Technische Hochschule Aachen
Aachen
NHR4CES@RWTH, in collaboration with NHR4CES@TUDa, focuses on providing hardware and scientific support, particularly for engineering applications and their interface with materials and the life sciences.
Key Expertise and Profile
- Flagship Collaboration: NHR4CES@RWTH and NHR4CES@TUDa bring together two NHR centers to combine their expertise and create strong synergies
- NHR4CES offer cutting-edge computing infrastructure with our state-of-the-art. Beyond outstanding hardware, dedicated experts offer scientific support and a wide range of training opportunities
- Cross-Sectional Groups (CSGs) and Simulation and Data Labs (SDLs) support researchers in using HPC innovatively
- The CSGs at NHR4CES@RTHW has advanced key methods relevant across HPC: from Data Engineering & AI to Parallelism & Performance, and Visualization
- The four NHR4CES@RWTH SDLs connect this expertise to specific fields such as Energy Conversion, Fluids, Materials Design, and Digital Patient, bridging infrastructure and application for impactful research.
NHR4CES@RWTH is also a member of the regional HPC.nrw competence network of North Rhine-Westphalia.
Technical Specifications
| Center Name | NHR4CES@RWTH |
|---|---|
| Total Resources: | |
| # CPU-Cores | 120 192 |
| # GPUs | 148 |
| Additional Information | |
| max. job run time [h] | 168 |
| jupyter notebook available [y/n] | y |
| CPU Resources: | |
| System 1 | CLAIX-2023 - HPC |
| CPU-Type | Intel Xeon 8468 |
| # nodes | 410 |
| # Cores per node | 96 |
| memory per node [GB] | 256 - 512 |
| System 2 | CLAIX-2025 - HPC |
| CPU-Type | ADM GENOA 9654 |
| # nodes | 421 |
| # Cores per node | 192 |
| memory per node [GB] | 384 - 768 |
| GPU Resources | |
| System 1 | CLAIX-2023 - ML |
| GPUs per node | 4 x NVIDIA H100 |
| # nodes | 31 |
| memory per GPU [GB] | 94 |
| System 2 | CLAIX-2025 - ML |
| GPUs per node | 4 x NVIDIA H100 |
| # nodes | 6 |
| memory per GPU [GB] | 80 |