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* Data driven decomposition
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* Fixed decomposition
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The fist approach try to generate a model for the interaction across processors and try to minimize the space
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The fist approach try to create a model for the interactions across processors and try to minimize the space
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The second instead try to divide the quantity of information the structure store without considering the interactions
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## Model decomposition
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The modular structure of OpenFPM give the possibility to create distributed structure with different decomposition strategies. |
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In a distributed-memory setting, where data are scattered across
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processors, two factors are important: equal division of work across
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processors and reduction of the communication overhead.
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A typical approach, is to formulate the problem as a
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graph-partitioning problem: the physical domain is divided into sub-domains
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(vertices of the graph), each of them carrying a weight modeling the computational cost.
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The communication pattern between sub-domains is represented as links
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between the sub-domains (edges of the graph) with weights formalizing
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the communication cost. The requirement of balanced computation with
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minimal communication then translates to the optimization problem of
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finding a graph partitioning where each group contains the same sum of
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weights, and the sum of the cut edges is minimal. Even if a model decomposition
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it is not bind to a graph model it is true that until now is the main approach
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* CartDecomposition |
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