Computational Modelling Group

Development of wide-ranging functionality in ONETEP

1st October 2009
Research Team
Jacek Dziedzic
Chris-Kriton Skylaris

Quantum mechanics has had a profound and pervasive influence on science and technology. Phenomena that are intrinsically quantum mechanical, such as magnetism, electron transport in semiconductors, and the effect of impurity atoms in materials, lie at the heart of almost every branch of industry. Quantum mechanical calculations of properties and processes from first-principles'' are capable of making accurate quantitative predictions but require solving the Schrdinger equation which is extremely difficult and can only be done using powerful computers. In contrast, empirical modelling approaches are relatively cheap but lack the predictive power of first-principles methods (which are parameter-free and take as input only the atomic numbers of the constituent atoms). The predictive capability is essential, in order to make rapid progress on new and challenging problems where there is insufficient experimental data and to also generate useful empirical approaches or even to check their reliability when these exist. Within the class of first-principles methods, one approach that has been outstandingly successful is the Density Functional Theory (DFT) as it combines high accuracy with moderate computational cost. Nevertheless, the computational effort of performing calculations with conventional DFT approaches increases as the cube of the number of atoms, making them unable to tackle problems with more than a few hundred atoms even on modern supercomputers. Since the pioneering work of the Nobel laureate Walter Kohn, it has been known that it is possible to reformulate DFT so that it scales linearly, which would in principle allow calculations with many thousands or even millions of atoms. The practical realisation of this however, in a method which is as robust and accurate as conventional cubic-scaling DFT approaches has been extremely difficult. The ONETEP approach developed over many years by the applicants of this proposal has achieved just that. ONETEP is at the cutting edge of developments in first principles calculations. However, while the fundamental difficulties of performing accurate first-principles calculations with linear-scaling cost have been solved, only a small core of functionality is currently available in ONETEP which prevents its wide application. In this collaborative project between three Universities, the original developers of ONETEP will lead an ambitious workplan whereby the functionality of the code will be rapidly and significantly enriched. The code development ethic of ONETEP, namely that software is robust, user-friendly, modular, portable and highly efficient on current and future HPC technologies will be of fundamental importance and will be further strengthened by rigorous cross-checking between the three institutions of this proposal. The developments are also challenging from a theoretical point of view as they need to be within the linear-scaling framework of ONETEP, using its highly non-trivial formulation of DFT in terms of in situ optimised localised functions. The program of work provides much added value as the few fundamental enabling technologies that will be developed in its first stages will then underpin many of the functional capabilities that will follow. The result will be a tool capable of a whole new level of materials simulation at the nanoscale with unprecedented accuracy. It will find immediate application in simulations in molecular biology, nanostructures and materials, which underpin solutions in urgent current problems such as energy, environment and health. Through the increasing number of commercial and academic users and developers of ONETEP, the worldwide dissemination and wide use of this novel tool will be rapid; finally the expanding ONETEP Developers' Group will coordinate the best strategies for the future maintenance and development of the software.


Life sciences simulation: Biomolecular simulations, Nanoscale Assemblies, Systems biology

Physical Systems and Engineering simulation: Energy, Materials, Metals, Semiconductors, Structural dynamics, Tribology

Algorithms and computational methods: Density functional Theory, FFT, Finite differences, Molecular Dynamics, Multi-physics, Multi-scale, Multigrid solvers

Simulation software: Onetep

Software Engineering Tools: SVN

Computational platforms: HECToR, Iridis, Linux

Transdisciplinary tags: Complex Systems, Computer Science, HPC, Scientific Computing, Software Engineering