Abstract
Two disjoint paradigms in scientific computing, namely adaptivity and parallelism respectively, have been combined, in order to achieve very high local resolution for climatological simulations. The basis for the simulation is a parallel adaptive unstructured triangular grid generator. Load balancing is achieved using a space-filling curve approach. The space-filling curve data partitioning shows a very desirable feature: It keeps data local even in a time-dependent simulation. Moreover, it is very fast and easily parallelizable.
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Behrens, J. (2001). Parallelizing an Adaptive Dynamical Grid Generator in a Climatological Trace Gas Transport Application. In: Sørevik, T., Manne, F., Gebremedhin, A.H., Moe, R. (eds) Applied Parallel Computing. New Paradigms for HPC in Industry and Academia. PARA 2000. Lecture Notes in Computer Science, vol 1947. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-70734-4_21
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DOI: https://doi.org/10.1007/3-540-70734-4_21
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