Distributed Percolation Analysis for Turbulent Flows

Research focus area – In Situ visualization and computational steering

Turbulent flow analysis plays a crucial role in many domains e.g. design of fuel-efficient cars and is an active research area primarily addressed through direct numerical simulations (DNS) of the Navier-Stokes equations. Percolation analysis studies the connectivity of sublevel-sets in derived scalar fields and has been proven useful to understand intense Reynolds stress or vorticity events. A major limitation of current approaches, however, is their slow runtime. To overcome this limitation, we at first devised an algorithm exploiting the union-find data structure, which is much faster. But since it is a global algorithm it is still challenging to parallelize. However, the size of turbulent-flow data requires analysis algorithms to run in parallel on distributed memory. This problem is addressed in our second algorithm working. It also builds upon the union-find data structure, however, keeping inter-process communication to a minimum by exploiting that many operations can be executed out-of-order and synchronization is only necessary a small number of times.