GPUGA

Graphics Processing Units Genetic Algorithm

What is GPUGA?

• GPUGA stands for Graphics Processing Units Genetic Algorithm. It is a code for empirical potential fitting using the genetic algorithm (GA).
• Using my laptop with a GeForce RTX 2070 GPU card, fitting an empirical potential using GPUGA only takes about one minute!

Prerequisites

• You need to have a GPU card with compute capability no less than 3.5 and a CUDA toolkit which supports your GPU card installed.
• I have only tested the code in linux operating system.

Compile GPUGA

• Go to the src directory and type make. When the compilation finishes, an executable named gpuga will be generated in the src directory.

Run GPUGA

• To run the provided example, go to the directory where you can see src and type src/gpuga < examples/input.txt
• The example corresponds to the case study for diamond silicon in the preprint below.

Citation

If you use GPUGA in your published work, we kindly ask you to cite the following paper which describes the central algorithms used in GPUGA:

• Zheyong Fan, Yanzhou Wang, Xiaokun Gu, Ping Qian, Yanjing Su, Tapio Ala-Nissila, A minimal Tersoff potential for diamond silicon with improved descriptions of elastic and phonon transport properties, https://arxiv.org/abs/1909.11474 Accepted to JPCM: https://iopscience.iop.org/article/10.1088/1361-648X/ab5c5f

Author:

• Zheyong Fan (Bohai University and Aalto University)
  • brucenju(at)gmail.com
  • zheyong.fan(at)aalto.fi
  • zheyongfan(at)163.com