The procedure for spatial sequential simulation – bi-point or multi-point stochastic simulation - of any type of variable starts with the definition of a random path which the simulation should follow in order to generate a structured image of an attribute. One problem of these algorithms is related to the effort a single processor is required to undertake, especially when applying to large grids.<br>With the advent of parallel computing and multi-core processors, it becomes clear that a scalable parallelization scheme can be developed to allow for considerable reduction in time spent performing simulations.<br>The idea is to partition the universe in a given number of sections, equal in number to double the number of processors or execution cores, in such a way that the locations to be concurrently simulated are sufficiently apart to be outside search range or multi-point template range. Their number depends on the size of the range, the number of nodes to be sequentially simulated and the number of available processors or execution cores. <br>The results of the proposed method were checked to evaluate if they succeeded to reproduce the spatial continuity and spatial patterns of the phenomenon and its distribution function with positive results.


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