**Parallelisation Support of a Large Eddy
Simulation Code**

NSC have started the code
parallelization support of prominent Swedish domain scientists. Scientists can
expect the increase of their problem sizes and the reduction of simulation time
by this service. This high-end collaboration between NSC and domain scientists
will strengthen international competitiveness of top-ranked Swedish scientists
and increase NSC¡¯s contribution to Swedish academia.

Prof. Lars Davidson¡¯s LES (Large Eddy
Simulation) fluid dynamics code has been chosen as a pilot project of this code
parallelization service. This code solves the incompressible Navier-Stokes
equations by solving decoupled velocity field (convection-diffusion equation)
and pressure field (pressure Poisson equation) iteratively. The
convection-diffusion solver uses the conventional 3-dimentional structured
stencil, while the pressure Poisson solver applies the multi-grid method and
stores the multi-level data on a 1-dimensional array. Minor changes are made on
the baseline code for the generic boundary condition imposition, effective
memory allocation, and the wall-distance function for the turbulence
computation. Mesh partitioner and communicators are implemented for the
parallel execution. A structured multi-block partitioner provides the load
balanced decomposition at the sufficient multi-grid levels. Communication
functions for structured 3-dimensional domains and 1-dimensional multi-grid
implementation are incorporated. These implementations are made generic for the
direct application to any mesh-based solvers.

Parallel performance has been measured
from a 3-dimensional flow simulation. The problem size is roughly 2.4 million
mesh points due to the memory allocation limit on a sequential code. As
presented in Figure 1, the speed-up ratio is linear (around 90% of parallel
efficiency) at small number of cores and it is maintained around 20 with more
processors, which shall be improved in the larger problem domain. We also
observe that algorithmic changes on time evolution scheme and the reduction of
boundary condition impositions on a baseline code will improve the parallel
performance with the convergence criteria, which shall be main objectives of a
next project.

This high-end user support provides the
opportunity of possessing well-tuned application codes to domain scientists. It
will accelerate the production of high-quality scientific researches.
Meanwhile, this cooperation requires the sufficient number of application
experts in individual scientific domain who is capable of dedicating this
long-term service. It necessitates more financial support for incrementing
application experts on various scientific domains.

Figure 1 Computation Time and the Speed-up of a
Parallelized LES Code