McCloud: Monte Carlo Cloud Service Framework provides a generic service implementation of Monte Carlo method, based on Microsoft Windows Azure, to solve a wide range of scientific and engineering problems.

The framework was developed in the context of the following master’s thesis:

• R. Nasser, McCloud service framework: development services of Monte Carlo simulation in the cloud, M.Sc. Dissertation, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, 2012 (in Portuguese)

The original code and documentation of the framework can be downloaded in the Codeplex official repository:

http://mccloud.codeplex.com

This GitHub repository stores the codes and results related to a Monte Carlo simulation in a structural system that was used as a benchmark test for the framework. Details can be seen in the following paper:

• A. Cunha Jr, R. Nasser, R. Sampaio, H. Lopes, and K. Breitman, Uncertainty quantification through Monte Carlo method in a cloud computing setting, Computer Physics Communications, v. 185, pp. 1355-1363, 2014 http://dx.doi.org/10.1016/j.cpc.2014.01.006

Authors

• Americo Cunha
• Rafael Nasser
• Rubens Sampaio
• Hélio Lopes
• Karin Breitman

Citing McCloud

We ask the code users to cite the following manuscript in any publications reporting work done with McCloud:

• R. Nasser, McCloud service framework: development services of Monte Carlo simulation in the cloud, M.Sc. Dissertation, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, 2012 (in Portuguese)
• A. Cunha Jr, R. Nasser, R. Sampaio, H. Lopes, and K. Breitman, Uncertainty quantification through Monte Carlo method in a cloud computing setting, Computer Physics Communications, v. 185, pp. 1355-1363, 2014 http://dx.doi.org/10.1016/j.cpc.2014.01.006

@mastersthesis{Nasser2012,
  author  = {R. Nasser},
  title   = { {McCloud} service framework: development services of {M}onte {C}arlo simulation in the cloud},
  school  = {Pontifícia Universidade Católica do Rio de Janeiro},
  year    = {2012},
  address = {Rio de Janeiro},
  note    = {(in Portuguese)},
}

@article{CunhaJr2014p1355,
  author  = {A. {Cunha~Jr} and R. Nasser and R. Sampaio and H. Lopes and K. Breitman},
  title   = {Uncertainty quantification through {M}onte {C}arlo method in a cloud computing setting},
  journal = {Computer Physics Communications},
  year    = {2014},
  volume  = {185},
  pages   = {1355-1363},
  doi     = {http://dx.doi.org/10.1016/j.cpc.2014.01.006},
}

Institutional support

Funding