Computing Resources
General Information
CAIDAS runs a High Performance Computing Cluster combined with a distributed big data storage on the premises of the University of Würzburg. The cluster allows distributed computations on large datasets for research purposes and big data applications. The considerable number of GPUs enable large scale machine learning experiments which are necessary for modern AI research.
Workloads are scheduled in containers through Kubernetes with Ceph providing a distributed filesystem. We also run Hadoop, HBase, and Accumulo within the cluster.
The current cluster also includes an NVIDIA DGX™ A100 system .
Technical data
| Nodes | 22 |
| Physical CPU cores | 1432 |
| Logical CPU cores | 2864 |
| GPUs | 71 |
| System Memory | 7900 GB |
| GPU Memory | 994 GB |
| Total Memory | 8834 GB |
| Theoretical Perfomance (FP32) | 950 TFLOPS |
| Distributed Storage Capacity | 1000 TB |
