A05
Integrating HPC-simulations with Data-Analysis for Structure Formation in Chemistry
The project aims to improve Ab initio molecular dynamics (AIMD) simulations and the analysis of their results for liquid systems in theoretical chemistry. The approach involves running multiple AIMD simulations simultaneously and using novel graph algorithms to exchange and analyze trajectory data. This will enable the study of more complex molecular systems and emergent structural properties. The goal is to make more efficient use of computer resources, improve application performance, and investigate complex chemical problems. The use of Modular Supercomputing Architecture (MSA) will match diverse workflow requirements and provide valuable insights for next-generation MSA-systems.
Barbara Kirchner
Professor of Theoretical Chemistry
Petra Mutzel
Professor of Computer Science
Petra Mutzel’s research focuses on the design, development, theoretical analysis and practical evaluation of new algorithms and data structures for combinatorial optimization problems on structured data that can be modeled as graphs or networks.
Estela Suarez
Professor of High Performance Computing
My research focuses on High Performance Computing, and in particular system level architecture, modular supercomputing, hardware prototyping and evaluation system software for HPC, analysis of operational data on HPC systems.