Abstract
There exist two widely used types of models for the investigation of flows in the world oceans: quasi-geostrophic (QG) models and models based on the primitive equations of motion (PE-models). Starting from existing sequential programs we investigate different strategies for their parallelization. Implementation strategies for the QG-model on a multiprocessor with shared memory and a few nodes are discussed. For the PE-model we describe an implementation on a distributed memory machine with special emphasis on the load balancing issue and communication costs.
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© 1994 Springer-Verlag Berlin Heidelberg
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Kersken, H.P., Fritzsch, B., Schenk, O., Hiller, W., Behrens, J., Krauße, E. (1994). Parallelization of large scale ocean models by data decomposition. In: Gentzsch, W., Harms, U. (eds) High-Performance Computing and Networking. HPCN-Europe 1994. Lecture Notes in Computer Science, vol 796. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020393
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DOI: https://doi.org/10.1007/BFb0020393
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