SKALB - Lattice-Boltzmann-Methoden für skalierbare Multi-Physik-Anwendungen

Internally funded project

Project Details

Project leader:
Prof. Dr. Ulrich Rüde

Project members:
Dr.-Ing. Christian Feichtinger

Contributing FAU Organisations:
Lehrstuhl für Informatik 10 (Systemsimulation)

Acronym: SKALB
Start date: 01/01/2009
End date: 31/12/2011

Abstract (technical / expert description):

The SKALB project is sponsored by the German Federal Ministry of Education and Research (BMBF). Its goal is the efficient implementation and further development of flow solvers based on the lattice Boltzmann method to allow large-scale simulation with complex multi-physics on petascale class computers. The lattice Boltzmann method is well accepted within the field of computational fluid dynamics (CFD). The main advantage of this numerical method is its simplicity which allows the simulation of flow in complex geometries like porous media or foams as well as highly efficient direct numerical simulations of turbulent flows. In the SKALB project lattice Boltzmann implementations should be methodically and technically further developed for the new class of large-scale heterogeneous and homogeneous parallel supercomputers. The HPC group of the Erlangen Regional Computing Center (RRZE) have long-standing expertise in performance modeling and efficient implementation of the lattice Boltzmann method on a broad spectrum of modern computers. They also work on new programming models and advanced optimization techniques for multi-/many-core processors. A full-grown lattice Boltzmann application code, which is under development at RRZE, is intended to be used in cooperation with Prof. Schwieger (Chair of Chemical Reaction Engineering) for massively parallel simulations of flow in porous media.

External Partners

Technische Universität Braunschweig


Feichtinger, C., Köstler, H., Hager, G., Rüde, U., Wellein, G., & Habich, J. (2011). A flexible Patch-based lattice Boltzmann parallelization approach for heterogeneous GPU-CPU clusters. Parallel Computing, 37(9), 536-549.
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Last updated on 2019-19-03 at 14:22