Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/americocunhajr/mccloud
McCloud provides a generic service implementation of Monte Carlo method, based on Microsoft Windows Azure, to solve a wide range of scientific and engineering problems.
https://github.com/americocunhajr/mccloud
cloud-computing mccloud monte-carlo-simulation parallel-computing structural-dynamics
Last synced: about 2 months ago
JSON representation
McCloud provides a generic service implementation of Monte Carlo method, based on Microsoft Windows Azure, to solve a wide range of scientific and engineering problems.
- Host: GitHub
- URL: https://github.com/americocunhajr/mccloud
- Owner: americocunhajr
- Created: 2020-07-19T02:59:00.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2024-07-18T03:27:12.000Z (6 months ago)
- Last Synced: 2024-07-18T23:30:04.423Z (6 months ago)
- Topics: cloud-computing, mccloud, monte-carlo-simulation, parallel-computing, structural-dynamics
- Language: MATLAB
- Homepage: https://americocunhajr.github.io/McCloud
- Size: 13.5 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
## Monte Carlo Cloud Service Framework
**McCloud: Monte Carlo Cloud Service Framework** is a powerful framework providing a generic implementation of the Monte Carlo method on Microsoft Windows Azure. It is designed to solve a wide range of scientific and engineering problems efficiently in the cloud.
### Table of Contents
- [Overview](#overview)
- [Features](#features)
- [Usage](#usage)
- [Authors](#authors)
- [Citing McCloud](#citing-mccloud)
- [Institutional Support](#institutional-support)
- [Funding](#funding)
### Overview
McCloud was developed as part 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 are available on the Codeplex repository:
[McCloud Codeplex Repository](http://mccloud.codeplex.com)
This GitHub repository includes codes and results from a benchmark Monte Carlo simulation on a structural system, detailed 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, 185, pp. 1355-1363, 2014. [DOI](http://dx.doi.org/10.1016/j.cpc.2014.01.006)
### Features
- Generic Monte Carlo service implementation
- Cloud-based computation using Microsoft Windows Azure
- Scalable and efficient solution for scientific and engineering simulations
- Extensive documentation and examples
### Usage
To get started with McCloud, follow these steps:
1. Clone the repository:
```bash
git clone https://github.com/americocunhajr/McCloud.git
```
2. Navigate to the code directory:
```bash
cd McCloud/McCloud
```
3. Execute:
```bash
McCloudProcess('3','0','case1a','case1a_process.csv')
McCloudMerge('3','case1a','case1a_process.csv','case1a_merge.csv')
sed -e "s/'//g" case1a_merge.csv > case1a_post.dat
McCloudPost('3','case1a','case1a_post.dat')
```
### Authors
- Americo Cunha
- Rafael Nasser
- Rubens Sampaio
- Hélio Lopes
- Karin Breitman
### Citing McCloud
If you use **McCloud** in your research, please cite the following publications:
- *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*
- *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)*
```
@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},
}
```
```
@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)},
}
```
### Institutional support
### Funding
