Rapid development of computer technologies has led to many core computer architectures with thousands of computational elements in a single device. In addition to the quantitative growth, these devices operate simultaneously and in parallel. In addition, if operation of one computational element is similar to the rational analysis of a human brain, the parallel operation of thousand such computational elements is capable to reproduce activity of a human brain at its intuitive level.
Thus, artificial neural networks inspired by the work of the human brain have received a powerful boost for their application at the forefront of modern science, primarily in the analysis of data obtained at the Large Hadron Collider in CERN (Geneva), where experiments in high energy and nuclear physics are aimed at studying a wide range of phenomena from the Higgs boson to the Big Bang and black holes.
The aim of the module is to learn detailed information and acquire skills in the areas:
- Experimental High Energy Physics and Heavy Ion Physics,
- HPC and many-core CPU/GPU computer architectures,
- Parallel programming compatible with advanced computer architectures,
- Artificial human-like thinking,
- The future of parallel computing.
- Trainer/in: Ivan Kisel
- Trainer/in: Kristin Neufeld
- Trainer/in: David Schneider
- Trainer/in: Raphael Skibka
- Trainer/in: Patrick Stärke