What is MILADY?
MILADY - Machine Learning DYnamics is a package created by scientists for scientists, aiming to improve the accuracy and predictive power of atomistic simulations. The code uses machine learning algorithms and prioritises methods with a reasonable computational cost. MILADY is an open-source code distributed under the Academic Software Licence (ASL).
Main functionalities:
Development of machine learning force fields, suitable for molecular dynamics simulations.
Development of surrogate regression models to predict materials properties, including vibrational entropy, HOMO-LUMO energies, etc.
Representation of atomic structures in the feature space of atomic descriptors.
Analysis, sparsification, and optimization of datasets.
Advantages of MILADY:
MILADY is designed for High Performance Computing and is therefore well parallelized and has a good scalability. It uses MPI, PBLAS and ScaLapack.
MILADY includes a large choice of atomic descriptors and regression models, including linear, quadratic, polynomial chaos, and kernels.
MILADY is open-source package and contributions are very welcome.
Contributors
The coupling of MILADY and LAMMPS was developed by Thomas D. Swinburne (CINaM, Marseille).
Contact
Questions and suggestions can be sent to our email. We will be happy to answer!
They appreciate and use MILADY
