v1.3.0 - Into the multi-GPU-niverse

[RandomDefaultUser]

New features

• Multi-GPU inference: Models can now make predictions on an arbitrary number of GPUs

• Multi-GPU training: Models can now be trained on an arbitrary number of GPUs

• MALA now works with 2D materials, i.e., any system which is only periodic in two dimensions

• Bispectrum descriptor calculation now possible in python

  • This is route is significantly slower than LAMMPS, but can be helpful for developers who want to test the entire MALA modeling workflow without installing LAMMPS

• Logging for network training has been overhauled and now allows for the logging of multiple metrics

• (EXPERIMENTAL) Implementation of a mutual information based metric to replace/complement the ACSD

• (EXPERIMENTAL) Implementation of a class for LDOS alignment to a reference energy value; this can be useful for models across multiple mass densities

Changes to API/user experience

• New parallelization parameters available:
  • use_lammps - enable/disable LAMMPS (enabled by default, recommended for optimal performance, will automatically be disabled if no LAMMPS is found on the machine)
  • use_atomic_density_formula - enable the use of total energy evaluation based on a Gaussian representation (enabled if LAMMPS and GPU are enabled, recommended for optimal performance, details can be found in our paper on size transfer)
  • use_ddp - enable/disable DDP, i.e., Pytorch's distributed training scheme (disabled by default)
• Multiple LAMMPS/QE calculations can now be run in one directory
  • Prior to this version, doing so would lead to problems due to the file based nature of these interfaces
  • This allows for multiple simultaneous inferences in the same folder
• Class SNAP and all associated options are deprecated, use Bispectrum and associated options instead
• Default units for reading from .cube files are now set to units commonly used within Quantum ESPRESSO, this should make it easier to avoid inconsistencies in data sampling
• ASE calculator MALA now reads models with load_run() instead of load_model which is more consistent with the rest of MALA
• Error reporting with the Tester class has been improved, all errors and energy values reported there are now consistently given in meV/atom
• MALA calculators (LDOS, density, DOS) now also read energy contributions and forces from Quantum ESPRESSO output files, these can be accessed via properties

Fixes

• Updated various performance/accessibility issues of CI/CD
• Fixed compatability with newer Optuna versions
• Added missing docstrings
• Fixed shuffling interface, arbitrary numbers of shuffled snapshots can now be created without loss of information
• Fixed inconsistency of density dimensions when using directly from cube file
• Fixed error when using GPU graphs with arbitrary batch sizes

[acangi]

Looks good to me. Fantastic job @RandomDefaultUser!

[RandomDefaultUser]

The CI is currently failing because there is an "internal server error" being sent back by RODARE... I don't know why that is, but it is most likely only a temporary problem of RODARE. I will resubmit the CI later today, and if the error persists, on Monday. It it persists thereafter, I will contact RODARE staff.

[srajama1]

Looks good to me, thank you @RandomDefaultUser !