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Mapping of ozone data with machine learning methods.

Differentiable, Hardware Accelerated, Molecular Dynamics

some ideas and proof-of-concepts for model output compression

Team1 Counting Leaf!

Material for High-performance computing with Python.

PRACE Workshop - Interactive High-Performance Computing with Jupyter

Interactive exploration and analysis of large amounts of data from scientific simulations, in-situ visualization and application control are convincing scenarios for explorative sciences. Based on the open source software JupyterLab, a way has been a

Interactive exploration and analysis of large amounts of data from scientific simulations, in-situ visualization and application control are convincing scenarios for explorative sciences. Based on the open source software JupyterLab, a way has been a

Explainable machine learning on the AQ-Bench dataset

Course material repository for the PRACE course "High Performance Scientific Computing in C++", 21 - 24 June 2021.

Microarchitectural benchmarks for optimizing compute throughput