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A path-level exact parallelization strategy for sequential simulation

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OA
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Ó
Óscar Peredo *
D
Daniel Baeza
J
Julián M. Ortíz
J
José R. Herrero
DOI:10.1016/j.cageo.2017.09.011delete
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Abstract

Abstract

En 中文
Sequential Simulation is a well known method in geostatistical modelling. Following the Bayesian approach for simulation of conditionally dependent random events, Sequential Indicator Simulation (SIS) method draws simulated values for K categories (categorical case) or classes defined by K different thresholds (continuous case). Similarly, Sequential Gaussian Simulation (SGS) method draws simulated values from a multivariate Gaussian field. In this work, a path-level approach to parallelize SIS and SGS methods is presented. A first stage of re-arrangement of the simulation path is performed, followed by a second stage of parallel simulation for non conflicting nodes. A key advantage of the proposed parallelization method is to generate identical realizations as with the original non-parallelized methods. Case studies are presented using two sequential simulation codes from GSLIB:SISIM and SGSIM. Execution time and speedup results are shown for large-scale domains, with many categories and maximum kriging neighbours in each case, achieving high speedup results in the best scenarios using 16 threads of execution in a single machine.
Keywords:
CONDITIONAL INDICATOR SIMULATION
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C
Computers and Geosciences
IF:
4.4
Papers:
5.0K
Citations:
1.5W

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queens university - canada
Scholars:
1.8W
Papers: 1.7W
Citations: 29
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universitat politecnica de catalunya
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universidad de chile
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