Uncertainty quantification through the Monte Carlo method in a cloud computing setting

@article{Cunha2014UncertaintyQT,
  title={Uncertainty quantification through the Monte Carlo method in a cloud computing setting},
  author={Americo Cunha and Rafael Nasser and Rubens Sampaio and H{\'e}lio C{\^o}rtes Vieira Lopes and Karin Koogan Breitman},
  journal={ArXiv},
  year={2014},
  volume={abs/2105.09512}
}
The Monte Carlo (MC) method is the most common technique used for uncertainty quantification, due to its simplicity and good statistical results. However, its computational cost is extremely high, and, in many cases, prohibitive. Fortunately, the MC algorithm is easily parallelizable, which allows its use in simulations where the computation of a single realization is very costly. This work presents a methodology for the parallelization of the MC method, in the context of cloud computing. This… Expand
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