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High Performance Computing

The modeling and numerical solution of scientific and industrial questions nowadays involve more detailed and complex models in order to address multi-physics problem settings, resolve complex spatial geometries, and meet accuracy requirements. The constantly growing computing resources on modern supercomputers provide the key infrastructure to numerically solve such large-sized models. The research group High Performance Computing focusses on the development and implementation of simulation methods and algorithms to efficiently address detailed and complex models using largest computing clusters and current architectures.



Research interests

  • Parallel simulation methods for continuum models based on partial differential equations (PDE)
  • Highly scalable iterative solvers for systems of equations steming from PDE based discretizations
  • Parallel, adaptive, geometric multigrid methods
  • Grid-based discretization methods (Finite Element, Finite Volume), higher order approaches
  • Software development (see ug4)