Abstract
The neural network approach for parallel construction of adaptive mesh on two-dimensional area is proposed. The approach is based on unsupervised learning algorithm for Kohonen’s Self Organizing Map and enables to obtain an adaptive mesh being isomorphic to a rectangular uniform one. A parallel algorithm for the construction of those meshes based on master-slave programming model is presented. The main feature of the obtained mesh is that their decomposition into subdomains required for parallel simulation on this mesh is reduced to partitioning of a rectangular array of nodes. The way of partitioning may be defined based on parallel simulations on the mesh. The efficiency of the parallel realization of the proposed algorithm is about 90%.
Supported by Presidium of Russian Academy of Sciences, Basic Research Program N17-6 (2004).
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Nechaeva, O. (2005). Neural Network Approach for Parallel Construction of Adaptive Meshes. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 2005. Lecture Notes in Computer Science, vol 3606. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11535294_39
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DOI: https://doi.org/10.1007/11535294_39
Publisher Name: Springer, Berlin, Heidelberg
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