Research infrastructure
Our research infrastructure supports data-intensive simulations, the training of AI models, the development of control algorithms, and hardware-related prototyping and system testing. It comprises modern server and HPC resources, a testbed for cyber-biological systems under real-world environmental conditions, and a fully equipped electronics and prototyping laboratory for the development of embedded systems.
Our lab provides modern infrastructure for the development and analysis of embedded systems, digital hardware, and small-scale power electronics. It includes fully equipped measurement workstations, debugging tools, and equipment for rapid hardware prototyping.
Digital Measurement Equipment
- Digital oscilloscope and digital multimeters
- Differential probe for power electronics
- Function and signal generator
- Logic analyzer
- Various debuggers and adapters for microcontroller development
Prototyping Equipment
- SMD soldering station and hot-air rework station
- ESD workstation including fume extraction
- Bambu Lab X1 Carbon for rapid 3D printing of prototypes
Our computing infrastructure supports data-intensive simulations, numerical optimization, and the training and testing of neural networks. It includes several GPU and CPU servers across different performance classes as well as an energy-efficient Apple-Silicon mini-cluster. Together, these resources enable both HPC workloads and distributed experiments as well as virtual development environments.
Apple-Silicon Mini-Cluster
- Specifications:
- 3 × Mac Mini M2 (8 GB RAM)
- 2 × Mac Mini M2 Pro (16 GB RAM)
- Use cases: Parallel simulations, AI prototyping, and energy-efficient development workloads
- Funding: Appointment funds of the University of Kassel
Server „hippo“ (High-end training & HPC)
| CPU | 2 × AMD EPYC 9755 (zusammen 256 Cores / 512 Threads) |
| Memory | 1.5 TB DDR5 RAM |
| Storage | 5 × 7.68 TB SSD |
| GPUs | 2 × NVIDIA H200 NVL GPUs (je 141 GB, NVLink) |
| Use cases | Large AI models, neural network training, HPC simulations, large optimization problems |
| Funding | Equipment Fund, University of Kassel |
| Usage | Shared with other research groups at the University of Kassel |
Server „rhino“ (GPU-accelerated AI workloads)
| CPU | AMD EPYC 9555 (64 Cores / 128 Threads) |
| Memory | 384 GB DDR5 RAM |
| Storage | 2 × 7.68 TB SSD |
| GPUs | 2 × NVIDIA A30 GPUs (je 24 GB) |
| Use cases | Training and inference of AI models, simulations, solving optimization problems |
| Funding | Equipment Fund, University of Kassel |
| Usage | Shared with other research groups at the University of Kassel |
Server „elephant“ (Virtualization & software testing)
| CPU | AMD EPYC 9374F (32 Cores / 64 Threads) |
| Memory | 192 GB DDR5 RAM |
| Storage | 4 × 3.84 TB SSD |
| Use cases | Virtual machines, continuous integration, simulations |
| Funding | Appointment funds of the University of Kassel |
Our testbed for cyber-biological systems consists of sensor- and actuator-equipped raised garden beds as well as a dedicated weather station. It enables us to investigate and validate system identification and control concepts, such as automatic, resource-efficient irrigation, under real-world environmental conditions.
Features
- Four raised bed environments, each equipped with
- 2 soil moisture sensors (ThetaProbe ML2x)
- 2 temperature sensors
- 2 pumps for local irrigation
- Weather station (based on the Raspberry Pi Weather Hat) with sensors for
- Wind speed
- Wind direction
- Temperature
- Humidity
- Solar irradiance
- Precipitation
We thank the Central Teaching Fund of the University of Kassel for supporting the establishment of this testbed. We would also like to thank the many students who made significant contributions to bringing the environment to life.