ase-fast 3.29.0b1

ASE-fast — Atomic Simulation Environment with Rust acceleration

ASE-fast is a drop-in replacement for ASE with optional Rust-accelerated hot paths. No code changes required — install the Rust extensions and every compatible call is automatically routed to the fast path.

Measured speedups on Apple M-series (arm64, Python 3.13):

Operation	Speedup
Neighbor list (scalar cutoff)	13.6×
Neighbor list (per-atom radii)	12.2×
Neighbor list (dict cutoffs)	9.1×
VASP POSCAR write	6.3×
VASP POSCAR read	3.3×
Extended XYZ write (large atoms)	3.5×
Simple XYZ write	2.3×
Minkowski reduction	2.6×

ASE is a set of tools and Python modules for setting up, manipulating, running, visualizing and analyzing atomistic simulations.

Upstream webpage: https://ase-lib.org/

Requirements

• Python 3.10 or later

• NumPy (base N-dimensional array package)

• SciPy (library for scientific computing)

• Matplotlib (2D Plotting)

Optional:

• Flask (for ase.db web-interface)

• spglib (for symmetry operations)

• Rust + maturin (to build the optional Rust fast-path extensions)

Installation

Pure-Python install (same as upstream ASE):

pip install ase

Development install from this repository:

pip install -e .

With Rust acceleration (recommended for MD / ML workflows):

You need a Rust toolchain (rustup) and maturin:

pip install maturin
# Build and install all four Rust extensions:
cd ase-neighborlist-rs && maturin develop --release && cd ..
cd ase-extxyz-rs       && maturin develop --release && cd ..
cd ase-geometry-rs     && maturin develop --release && cd ..
cd ase-io-rs           && maturin develop --release && cd ..

That’s it. All Rust crates live inside the repository alongside the Python source. After building, ASE automatically detects the extensions and enables the fast paths — no configuration needed.

To verify the extensions are active:

python -c "
import ase.neighborlist as nl
import ase.io.extxyz as ex
import ase.geometry.minkowski_reduction as mk
import ase.io.vasp as vasp
print('NL Rust:', nl._HAVE_RUST_NEIGHBORLIST)
print('extxyz Rust:', ex._HAVE_RUST_EXTXYZ)
print('geometry Rust:', mk._HAVE_RUST_GEOM)
print('VASP IO Rust:', vasp._HAVE_RUST_IO)
"

Running benchmarks:

python benchmarks/run_benchmarks.py                   # full suite
python benchmarks/run_benchmarks.py --quick           # fewer reps
python benchmarks/run_benchmarks.py --output out.json # save results

Testing

Please run the tests:

$ ase test  # takes 1 min.

and send us the output if there are failing tests.

Contact

• Mailing list: ase-users

• Chat: Join the #ase channel on Matrix, also accessible via the Element webclient.

• There is an ASE forum on the Materials Science Community Forum.

Feel free to create Merge Requests and Issues on our GitLab page: https://gitlab.com/ase/ase

For regular support, please use the mailing list or chat rather than GitLab.

Example

Geometry optimization of hydrogen molecule with NWChem:

>>> from ase import Atoms
>>> from ase.optimize import BFGS
>>> from ase.calculators.nwchem import NWChem
>>> from ase.io import write
>>> h2 = Atoms('H2',
               positions=[[0, 0, 0],
                          [0, 0, 0.7]])
>>> h2.calc = NWChem(xc='PBE')
>>> opt = BFGS(h2, trajectory='h2.traj')
>>> opt.run(fmax=0.02)
BFGS:   0  19:10:49    -31.435229     2.2691
BFGS:   1  19:10:50    -31.490773     0.3740
BFGS:   2  19:10:50    -31.492791     0.0630
BFGS:   3  19:10:51    -31.492848     0.0023
>>> write('H2.xyz', h2)
>>> h2.get_potential_energy()  # ASE's units are eV and Ang
-31.492847800329216

This example requires NWChem to be installed.

$ ase gui h2.traj

Contributors

• Original ASE team (DTU Physics and many others) — see upstream AUTHORS file

• Andrei Voicu Tomut — Rust acceleration layer (ase-fast), type hints, error messages, LLM builder