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Data for A universal preconditioner for simulating condensed phase materials

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Packwood, David, Kermode, James R., Mones, Letif, Bernstein, Noam, Woolley, John, Gould, Nicholas, Ortner, Christoph and Csanyi, Gabor (2016) Data for A universal preconditioner for simulating condensed phase materials. [Dataset]

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Official URL: http://wrap.warwick.ac.uk/78579

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Abstract

We introduce a universal sparse preconditioner that accelerates geometry optimisation and saddle point search tasks that are common in the atomic scale simulation of materials. Our preconditioner is based on the neighbourhood structure and we demonstrate the gain in computational efficiency in a wide range of materials that include metals, insulators and molecular solids. The simple structure of the preconditioner means that the gains can be realised in practice not only when using expensive electronic structure models but also for fast empirical potentials. Even for relatively small systems of a few hundred atoms, we observe speedups of a factor of two or more, and the gain grows with system size. An open source Python implementation within the Atomic Simulation Environment is available, offering interfaces to a wide range of atomistic codes.

Item Type: Dataset
Subjects: Q Science > QA Mathematics
Q Science > QC Physics
Divisions: Faculty of Science, Engineering and Medicine > Engineering > Engineering
Faculty of Science, Engineering and Medicine > Science > Mathematics
Faculty of Science, Engineering and Medicine > Science > Physics
Library of Congress Subject Headings (LCSH): Condensed matter -- Computer simulation, Mathematical optimization
Publisher: University of Warwick, School of Engineering
Official Date: 20 April 2016
Dates:
DateEvent
20 April 2016Available
4 April 2016Accepted
Status: Not Peer Reviewed
Publication Status: Published
Media of Output (format): .txt .xlsx
Access rights to Published version: Open Access (Creative Commons)
Description:

## Required software

- ASE (currently `jameskermode` fork needed, will shortly be merged into ASE trunk):

git clone https://gitlab.com/jameskermode/ase
cd ase
git checkout precon
python setup.py install

- Jupyter notebook:

pip install jupyter

- QUIP/quippy (optional, for some of the interatomic potentials):

git clone https://github.com/libAtoms/QUIP
cd QUIP
make config
make
make quippy
make install-quippy

- MatSciPy (optional, for fast neighbour lists):

git clone https://github.com/libAtoms/matscipy
cd matscipy
python setup.py install

- PyAMG (optional, for fast preconditioner inversion/application):

pip install pyamg

- Some of the tests also require VASP, CASTEP or CP2K DFT codes
- Some of the notebooks require Julia (v0.4.x)

## General files
README-dataset.txt - this file
notebooks/plots.ipynb - Jupyter notebook (Python)

## Data files for Fig. 1
notebooks/spectra3.ipynb - Jupyter notebook (Julia)

## Data files for Fig. 2
Si_slab/quip_params.xml - SW force field parameters
Si_slab/test_precon.xyz - input structure
Si_slab/results.new.C1_Exp_3.0_Pfrommer_ID.json - results (all cases)
Si_slab/run.py - Python script

## Data files for Fig. 3
Si_crack/params.xml - SW force field parameters
Si_crack/crack.xyz - input structure
Si_crack/crack.json - results (ID, A=0, A=3 preconditioners)
Si_crack/crack_Pfrommer.json - results (Pfrommer preconditioner)
Si_crack/test-crack.ipynb - Jupyter notebook

## Data files for Fig. 4
notebooks/precon-scaling.ipynb - Jupyter notebook (Python)

## Data files for Fig. 5

PAW setups used are from the vasp 4.6 distribution: regular La and Al, and O_s (soft).

LaAlO3_crack/LaAlO3_crack.c0.xyz - input structure
LaAlO3_crack/KPOINTS - VASP kpoint mesh
LaAlO3_crack/run.py - Python script
LaAlO3_crack/results.ID.json - results
LaAlO3_crack/results.C1.json - results
LaAlO3_crack/results.Exp_3.0.json - results
LaAlO3_crack/results.Pfrommer.json - results

## Data files for Fig. 6

PAW setups used are from the vasp 4.6 distribution: regular Al, but the conventional O.

gamma_Al2O3/gamma_Al2O3_Johannes_1.01.c0.xyz 0 input structure
gamma_Al2O3/INCAR.template - VASP input file
gamma_Al2O3/run.py - Python script
gamma_Al2O3/results.C1.json - results
gamma_Al2O3/results.Exp_3.0.json - results
gamma_Al2O3/results.ID.json - results
gamma_Al2O3/results.Pfrommer.json - results

## Data files for Fig. 7

ice/run/run.py - Python script
ice/run/common/BASIS_SET - CP2K input
ice/run/common/cp2k_input_force.template - CP2K input
ice/run/common/iceVIII.xyz - CP2K input
ice/run/common/POTENTIAL - CP2K input
ice/results/dump.json.VIIIbig.geom.new_preconpy_cp2k_force_preconLBFGS_ID_fmax_0.001_armijo - results
ice/results/dump.json.VIIIbig.geom.new_preconpy_cp2k_force_preconLBFGS_Exp_A_0.0_rcut_2.25_fmax_0.001_armijo - results
ice/results/dump.json.VIIIbig.geom.new_preconpy_cp2k_force_preconLBFGS_Exp_A_3.0_fmax_0.001_armijo - results
ice/results/dump.json.VIIIbig.geom.cell.new_preconpy_cp2k_force_stress_preconLBFGS_ID_fmax_0.001_armijo - results
ice/results/dump.json.VIIIbig.geom.cell.new_preconpy_cp2k_force_stress_preconLBFGS_Exp_A_0.0_rcut_2.25_fmax_0.001_armijo - results
ice/results/dump.json.VIIIbig.geom.cell.new_preconpy_cp2k_force_stress_preconLBFGS_Exp_A_3.0_fmax_0.001_armijo - results

## Data files for Fig. 8
notebooks/dimer-fig.ipynb - Jupyter notebook (Julia)

RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
EP/J022055/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
EP/L014742/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
EP/L027682/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
EP/J010847/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
EP/J021377/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
DE-AC02-06CH11357Great Britain. Department of the Environmenthttps://viaf.org/viaf/127761923
UNSPECIFIEDOffice of Naval Researchhttp://dx.doi.org/10.13039/100000006
335120H2020 European Institute of Innovation and Technologyhttp://dx.doi.org/10.13039/100010686
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