Abstract
We propose in this paper, a parallel implementation of a ground visualization algorithm. Our input data consist in a Digital Elevation Model (DEM) covering a rectangular region, together with a raster image of the same area (the texture). The goal of the algorithm is to compute in parallel, images of the DEM from any point of view while mapping the texture onto the surface. The main originality of our approach concerns the distribution of the data, leading to a load-balanced and scalable parallel algorithm. We use a workload estimation to partition the output image, and then redistribute the input data according to this division. Special attention is paid on the data structures used for minimizing the cost of communications.
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