期刊
JOURNAL OF CHEMICAL PHYSICS
卷 144, 期 16, 页码 -出版社
AMER INST PHYSICS
DOI: 10.1063/1.4947024
关键词
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资金
- Engineering and Physical Sciences Research Council (EPSRC) [EP/J022055/1, EP/L014742/1, EP/L027682/1, EP/J010847/1, EP/J021377/1]
- Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility [DE-AC02-06CH11357]
- Office of Naval Research through the Naval Research Laboratory's basic research program
- ERC [335120]
- EPSRC [EP/K014560/1, EP/L027682/1, EP/J021377/1, EP/J022012/1, EP/J022055/1, EP/J010847/1, EP/L014742/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/L014742/1, EP/J022012/1, EP/K014560/1, EP/J022055/1, EP/J010847/1, EP/J021377/1, EP/L027682/1] Funding Source: researchfish
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. (C) 2016 Author(s).
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