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@BOOK{Baumeister:128376,
author = {Baumeister, Paul Ferdinand},
title = {{R}eal-{S}pace {F}inite-{D}ifference {PAW} {M}ethod for
{L}arge-{S}cale {A}pplications on {M}assively {P}arallel
{C}omputers},
volume = {53},
school = {RWTH Aachen},
type = {Dr. (Univ.)},
address = {Jülich},
publisher = {Foschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
reportid = {FZJ-2013-00115},
isbn = {978-3-89336-836-5},
series = {Schriften des Forschungszentrums Jülich.
Schlüsseltechnologien / Key Technologies},
pages = {VI, 212 S.},
year = {2012},
note = {Schriftenreihen des Forschungszentrum Jülich; RWTH Aachen,
Diss., 2012},
abstract = {Simulations of materials from first principles have
improved drastically over the last few decades, benefitting
from newly developed methods and access to increasingly
large computing resources. Nevertheless, a quantum
mechanical description of a solid without approximations is
not feasible. In the wide field of methods for $\textit{ab
initio}$ calculations of electronic structure, it has become
apparent that density functional theory and, in particular,
the local density approximation can also make simulations of
large systems accessible. Density functional calculations
provide insight into the processes taking place in a vast
range of materials by their access to an understandable
electronic structure in the framework of the Kohn-Sham
single particle wave functions. A number of functionalities
in the fields of electronic devices, catalytic surfaces,
molecular synthesis and magnetic materials can be explained
by analyzing the resulting total energies, ground state
structures and Kohn-Sham spectra. However, challenging
physical problems are often accompanied by calculations
including a huge number of atoms in the simulation volume,
mostly due to very low symmetry. The total workload of
wave-function-based DFT scales at best quadraticallywith the
number of atoms. This means that supercomputersmust be used.
In the present work, an implementation of DFT on real-space
grids has been developed, suitable for making use of the
massively parallel computing resources of modern
supercomputers. Massively parallel machines are based on
distributed memory and huge numbers of compute nodes, easily
exceeding 100,000 parallel processes. An efficient
parallelization of density functional calculations is only
possible when the data can be stored process-local and the
amount of inter-node communication is kept low. Our
real-space grid approach with three-dimensional domain
decomposition provides an intrinsic data locality and solves
both the Poisson equation for the electrostatic problemand
the Kohn-Sham eigenvalue problem on a uniform real-space
grid. The derivative operators are approximated by finite
differences leading to localized operators which only
require communication with the nearest neighbor processes.
This leads to excellent parallel performance at large system
sizes. Treating only valence electrons, we apply the
projector-augmented wave method for accurate modeling of
energy contributions and scattering properties of the atomic
cores. In addition to real-space grid parallelization, we
apply a distribution of the workload of different Kohn-Sham
states onto parallel processes. This second parallelization
level avoids the memory bottleneck for large system sizes
and introduces even more parallel speedup. Calculations of
systems with up to 3584 atoms of Ge, Sb and Te were
performed on (up to) all 294,912 cores of JUGENE, the
massively parallel supercomputer installed at
Forschungszentrum Jülich.},
cin = {PGI-1 / IAS-1},
cid = {I:(DE-Juel1)PGI-1-20110106 / I:(DE-Juel1)IAS-1-20090406},
pnm = {422 - Spin-based and quantum information (POF2-422)},
pid = {G:(DE-HGF)POF2-422},
typ = {PUB:(DE-HGF)3},
url = {https://juser.fz-juelich.de/record/128376},
}