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N-body Simulation OpenMp

In physics and astronomy, an N-body simulation is a simulation of a dynamical system of particles, usually under the influence of physical forces, such as gravity. N-body simulations are widely used tools in astrophysics, from investigating the dynamics of few-body systems like the Earth-Moon-Sun system to understanding the evolution of the large-scale structure of the universe. Here, we have achieved the same assuming n bodies are trapped inside a cuboid of given dimensions using OpenMp.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

What things you need to install the software and how to install them

OpenMp
Python >= 2.7
Mayavi
Pygame

Installing

A step by step series of examples that tell you how to get a development env running. In the terminal execute the following commands.

For installing OpenMp


$sudo apt-get install libomp-dev

For installing mayavi


$sudo easy_install pip<br/>
$sudo pip install mayavi

For installing pygame


$sudo apt-get install python-pygame

Pygame is used for 2D visualisation whereas mayavi is used for 3D visualisation.

Running the simulation

In order the simulate the environment, one needs to do the following:

Generating Trajectory file

This generates trajectory file for the specified number of threads which will be visualised.


$g++ -fopenmp many_body.cpp -o generate <br/>
$./generate number_of_threads

Specify the number of threads you want the code to run on in place of "number_of_threads".

Visualisation

Run the following commands for visualisation after trajectory file is generated.

For 2D Visualisation

$python2 visualiser.py 1

For 3D Visualisation

$python2 visualiser.py 2

Contributing

Please feel free to contribute by sending in PR and opening and handling issues.

Authors

See the list of contributors who participated in this project.

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

  • This project was made as a part of the course High Performance Parallel Programming.

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