High-Performance Computing (HPC), FHNW School of Computer Science

We develop high-performance algorithms for data- and compute-intensive applications in science, engineering, and industry. A central focus is the efficient parallelisation of programs on distributed systems — across clusters, cloud infrastructures, and specialised HPC environments.

A particular strength lies in the close integration of High-Performance Computing (HPC) with Artificial Intelligence methods. We combine classical numerical approaches with modern AI workloads, for example in image processing, the simulation of physical processes, or the analysis of large-scale scientific datasets. By leveraging hybrid architectures (CPU/GPU), we aim to achieve maximum performance while ensuring high energy efficiency.

Our expertise includes:

• GPU-optimised algorithms and data pipelines
• AI-accelerated simulation and modelling
• Scalable training and inference environments for modern models
• Design and operation of robust, production-grade HPC systems

With our own high-performance computing system, we operate a powerful infrastructure that reliably supports research and industry projects — including compute-intensive AI experiments and large-scale simulations.