The Training and Scalable Algorithms (TASC) group is responsible for the organization and implementation of the training activities at HLRS. We provide training courses and educational services for a variety of topics from the areas of high-performance computing, artificial intelligence, and modeling & simulation:
In each area, our goal is to provide an outstanding learning experience by offering training on relevant topics, with up-to-date and audience-focused content, and given by highly-qualified instructors.
Besides our teaching and outreach activities, we conduct research on the development of efficient algorithms for scientific computing applications. Here, our focus is on finding portable approaches that scale well across different domain areas, over heterogeneous hardware configurations, and on parallel systems. Of particular interest is the Julia programming language, which combines ease-of-use with efficient, highly scalable implementations.
Lorenzo Zanon
Research Scientist
Head, Training & Scalable Algorithms
This project coordinates support for HPC users in Baden-Württemberg and the implementation of related measures and activities, including data intensive computing and large-scale scientific data management.
CASTIEL 2 facilitates collaboration among the EuroCC 2 National Competence Centers and the EuroHPC Joint Undertaking Centers of Excellence, promoting the development of HPC expertise and the adoption of leading codes across Europe.
Supported by the EuroHPC Joint Undertaking, EuroCC 2 manages a European network of National Competence Centers (NCC) for high-performance computing and related technologies, promoting a common level of expertise across the participating countries.
EXCELLERAT P2 is developing advanced applications for engineering in the manufacturing, energy, aeronautics, and automotive sectors, focusing on use cases that demonstrate the importance of HPC, HPDA, and AI for European competitiveness.
The HiDALGO2 project is addressing challenges caused by climate change, focusing on technical issues related to scalability on HPC and AI infrastructures, the use of computational fluid dynamics methods, and uncertainty analysis.
HLRS is the coordinating center for this project to integrate artificial intelligence (AI) topics into curricula at the University of Stuttgart, and to implement AI technologies to improve instruction.
The SEQUOIA End-to-End project aims to develop transparent, automated, and controllable end-to-end solutions for the industrial use of hybrid quantum applications and algorithms through holistic quantum software engineering.
This enrichment program offers school-age students opportunities to develop and execute simulation projects in collaboration with HLRS scientists.
SiVeGCS coordinates and ensures the availability of HPC resources of the Gauss Centre for Supercomputing, addressing issues related to funding, operation, training, and user support across Germany's national HPC infrastructure.
