Parallel multigrid methods are very prominent tools for solving huge
systems of (non-)linear equations arising from the discretisation of
PDEs, as for instance in Computational Fluid Dynamics (CFD). The
superiority of multigrid methods in regard of numerical complexity
mainly stands and falls with the smoothing algorithms (`smoother`)
used. Since the inherent highly recursive character of many global
smoothers (SOR, ILU) often impedes a direct parallelisation, the
application of block smoothers is an alternative. However, due to the
weakened recursive character, the resulting parallel efficiency may
decrease in comparison to the sequential performance, due to a weaker
total numerical efficiency. Within this paper, we show the
consequences of such a strategy for the resulting total efficiency if
incorporated into a parallel CFD solver for 3D incompressible
flow. Moreover, we compare this parallel version with the related
optimised sequential code in FEATFLOW and we analyse the numerical
losses of parallel efficiency due to communication costs, numerical
efficiency and finally the choice of programming language (C++ vs./
F77). Altogether, we obtain quite surprising, but more realistic
estimates for the total efficiency of such a parallel CFD tool in
comparison to the related `optimal` sequential version.