Abstract
Two different strategies are discussed, for the partitioning of composite grids, in the context of parallel computers of MIMD type with distributed memory. The two strategies are compared theoretically, with respect to arithmetic load balance and communication overhead. Moreover, the ability to handle dynamically changing grids is considered. Composite, structured grids are the natural choice for finite difference methods on complicated geometries, which can not be covered by a single, structured grid. A composite grid is a union of (in general curvilinear) structured grids. So called multi-block grids, frequently used, e.g., in aerodynamical computations, constitute a special case. The discussion in the present paper is valid also if the blocks are unstructured, and for hybrids such as dragon grids. Composite grids are more complicated to partition than single grids. The present paper points out the difficulties in detail, giving some quantification of the overhead that may result from a naive implementation of composite grid partitioning. These results indicate what are the crucial implementation issues in the present context.
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