MicroSim is a software stack that consists of phase-field codes that offer flexibility with discretization, models as well as the high-performance computing hardware(CPU/GPU) that they can execute on. Along with this the stack also consists of Multi-physics solver modules that are based on OpenFoam and AMRex libraries(will be added soon). The stack has an integrator interface that is built using python that allows one to create the input and filling files required for the solvers as well as provides a consolidated framework to choose the solver, compile, execute and visualize simulation results. The project is a consortium between (IISc Bangalore, IIT Hyderabad, IIT Bombay, IIT Madras, Savitribai Phule Pune University, C-DAC Pune). Following is a brief description of the different software modules and details on how to independently execute them.
This is multiphase multi-component phase-field solver based on the grand-potential formalism. This is a 2D serial CPU version of the code.
Compilation can be done by a simple "make".
For running the following execution command is required
./microsim_gp name_of_infile name_of_filling_file name_of_output_files
The files are written in the DATA folder in the .vtk format.
The code has been developed at IISc Bangalore, Department of Materials Engineering by Prof. Abhik Choudhury.
This is multiphase multi-component phase-field solver based on the grand-potential formalism. The solver is parallelized using MPI on CPUs and requires the h5pcc compiler for compilation and execution.
Compilation can be done by a simple "make"
For running the code on the cluster please use a script. For testing on your desktops/laptops the following execution command is required
mpirun -np num_processors ./microsim_gp name_of_infile name_of_filling_file name_of_output_files num_workers_x num_workers_y
For .h5 files, with WRITEHDF5=1, output files need to be transformed in .xml format using the following command just above the DATA folder that is created upon execution
./write_xdmf name_of_infile name_of_output_file total_no_workers start_time end_time
For ASCII files in .vtk format the consolidated output files needs to be reconstructed out of separate processor files that are written in the DATA folder that is created upon execution
./reconstruct name_of_infile name_of_output_file number_of_workers start_time end_time
The code has been developed at IISc Bangalore, Department of Materials Engineering by Prof. Abhik Choudhury.
The code is built on work by past PhD students
a) Sumeet Rajesh Khanna
- C code for precipitate evolution.
- It solves Allen-Cahn and Cahn–Hilliard equations using FFTW3.
- Compile the code using "make". Compilation creates "FFT_2D_ppt.out" file.
- Execute "./microsim_ch_fft Input.in Filling.in output"
- Authors: Dasari Mohan and M P Gururajan
- This is alpha version of the code and check for updates in future release.
- Copyright (c) 2021 Materials and Process Modelling Laboratory,
- Department of Metallurgical Engineering and Materials Science,
- Indian Institute of Technology Bombay, Mumbai 400076 INDIA.
This code solves the problem of precipitate growth using a multiphase field solver on the GPU. The code is tested on Tesla P100 and Tesla V100. For Tesla K80, one needs to comment "CudaMemPrefetchAsync" in solverloop/evolve.h
To run the code use
- "make" to create executable microsim_kks_cufft
- Execute "./microsim_kks_cufft Input.in Filling.in Output"
The code uses CUDA version 11, CUFFT and CUDA-CUB libraries. nvcc version 11.2 is used for compilation of the codes. Input.in contains all numerical and physical parameters used in the simulations. Makefile creates a DATA folder where the datafiles (in the form of VTK files) are stored. VTK files can be viewed using Paraview.
This is the alpha version of code. We will continue to add more features in future release.
- GPU Phase-Field Developer Team @ IITH (Pankaj, Saurav Shenoy, Saswata Bhattacharya)
The following contributers are acknowledged
- Tushar Jogi
- Hemanth Kumar Sandireddy
- OpenCL code for solidification microstructure evolution
- Compile the code using "make". Compilation creates "kim_soldfn.out" file.
- GEdata_writer.py is used for generation of Gibbs energy and its derivatives
- To generate Gibbs energies and execute the program
- run "./kimsldfn.sh Input.in Filling.in Output"
- It is always safe to run above command for execution of the code.
- If Gibbs energies are generated already then generating
- Gibbs energies can be skipped and directly execute following command.
- Execute "./microsim_kks_opencl Input.in Filling.in Output"
- Authors: Dasari Mohan and G Phanikumar
- Acknowledgement to P. Gerald Tennyson for contributions towards code development at IITM
- This is alpha version of the code and check for updates in future release.
This repository is a fork of Phase-Field-DynamicMeshing. The addition primarily is the documentations. The description of each directories are given below:
It contains the Doxygen configuration file, generated HTML and LaTeX documentation files from the source codes. To access HTML documentation, open html/index.html. To access LaTeX generated PDF documentation, open pdflatex/refman.pdf.
It contains the source files of the solver.
It contains the R Markdown files for creating the HTML (userGuide.html) and PDF (userGuide.pdf) documentations of the OpenFOAM cases.
It contains the OpenFOAM case files required to run the free growth problem.
It contains the OpenFOAM case files required to run the directional solidification problem.
Python GUI application for generating Infile and Filling files.
- Python v3.5 and later
- pyqt5 Library
To check the version installed, open a terminal window and entering the following:
python --version
If installed python version is 3.5 or above then you can continue to install pyqt5 library using pip. To install python or upgrade older python version follow next step -
Download setup from https://www.python.org/downloads/ and follow the instruction.
If you are using Ubuntu 16.10 or newer, then you can easily install Python 3 with the following commands:
sudo apt-get update
sudo apt-get install python3
If you’re using another version of Ubuntu (e.g. the latest LTS release) or you want to use a more current Python, we recommend using the deadsnakes PPA to install Python 3:
sudo apt-get install software-properties-common
sudo add-apt-repository ppa:deadsnakes/ppa
sudo apt-get update
sudo apt-get install python3
If you are using other Linux distribution, chances are you already have Python 3 pre-installed as well. If not, use your distribution’s package manager. For example on Fedora, you would use dnf:
sudo dnf install python3
Download the https://bootstrap.pypa.io/get-pip.py file and store it in the same directory as python is installed. Run the command given below: python get-pip.py and wait through the installation process.
To Install PIP3(For Python 3+):
sudo apt install python3-pip
pip install --upgrade pip
pip install pyqt5
To run the code use python ./InfileGenerator.py
Developed by- Ajay Sagar