Optimizing performance of the lattice Boltzmann method for complex structures on cache-based architectures

Delivering high sustained performance for memory-intensive applications in computa-tional fluid dynamics on cache-based microprocessors is a long-standing challenge. In particular, non regular data access patterns, as arising from porous media flow within lattice Boltzmann codes, can lead to poor performance. To address this problem, we combine a 1-D list data representation with advanced code optimizations and are able to achieve a high performance level, which is mostly independent of geometry and obstacle/fluid ratio. The idea of traversing memory using space-filling curves is tested as well, but our results indicate that this approach alone can not compete with standard techniques, i.e. blocking and data layout optimization, which become architecture de-pendent if an indirect memory addressing scheme is being used.