In the presented approach, the parallelization strategy is based again on the domain decomposition concept. The domain decomposition, however, has been considered on two levels - the model level and the model entity parametric tree level. The decomposition on model level splits the model into domains on the model entity basis. Each model entity which does not form boundary of another model entity of higher dimension (these entities are called the relevant model entities thereafter) constitutes an individual domain. The advantage of this approach consists in the fact that the decomposition is in agreement with the physical concept of the model (the model boundaries coincide with the interprocessor boundaries). The decomposition on the parametric tree level may be compared, in some sense, with the ORB in the parametric space of a given model entity. Since the splitting is done in the parametric space its image in the real space does not generally result in domains of similar size. The next bisection, however, may be applied to larger (or more complex) from those domains etc. In this way, an arbitrary number of domains, with no one exceeding a prescribed value of complexity, may be created. This is a good starting point to achieve acceptable parallel performance for various number of processors and varying model complexity. An important fact is that all the domains can be handled uniquely as model entity domain because they are described by the same model entity and differs only in the range of parametric coordinates.

*Daniel Rypl
2005-12-03*