7,757 research outputs found
Extensions of the siesta dft code for simulation of molecules
We describe extensions to the siesta density functional theory (dft) code
[30], for the simulation of isolated molecules and their absorption spectra.
The extensions allow for: - Use of a multi-grid solver for the Poisson equation
on a finite dft mesh. Non-periodic, Dirichlet boundary conditions are computed
by expansion of the electric multipoles over spherical harmonics. - Truncation
of a molecular system by the method of design atom pseudo- potentials of Xiao
and Zhang[32]. - Electrostatic potential fitting to determine effective atomic
charges. - Derivation of electronic absorption transition energies and
oscillator stren- gths from the raw spectra produced by a recently described,
order O(N3), time-dependent dft code[21]. The code is furthermore integrated
within siesta as a post-processing option
ELSI: A Unified Software Interface for Kohn-Sham Electronic Structure Solvers
Solving the electronic structure from a generalized or standard eigenproblem
is often the bottleneck in large scale calculations based on Kohn-Sham
density-functional theory. This problem must be addressed by essentially all
current electronic structure codes, based on similar matrix expressions, and by
high-performance computation. We here present a unified software interface,
ELSI, to access different strategies that address the Kohn-Sham eigenvalue
problem. Currently supported algorithms include the dense generalized
eigensolver library ELPA, the orbital minimization method implemented in
libOMM, and the pole expansion and selected inversion (PEXSI) approach with
lower computational complexity for semilocal density functionals. The ELSI
interface aims to simplify the implementation and optimal use of the different
strategies, by offering (a) a unified software framework designed for the
electronic structure solvers in Kohn-Sham density-functional theory; (b)
reasonable default parameters for a chosen solver; (c) automatic conversion
between input and internal working matrix formats, and in the future (d)
recommendation of the optimal solver depending on the specific problem.
Comparative benchmarks are shown for system sizes up to 11,520 atoms (172,800
basis functions) on distributed memory supercomputing architectures.Comment: 55 pages, 14 figures, 2 table
Computation- and Space-Efficient Implementation of SSA
The computational complexity of different steps of the basic SSA is
discussed. It is shown that the use of the general-purpose "blackbox" routines
(e.g. found in packages like LAPACK) leads to huge waste of time resources
since the special Hankel structure of the trajectory matrix is not taken into
account. We outline several state-of-the-art algorithms (for example,
Lanczos-based truncated SVD) which can be modified to exploit the structure of
the trajectory matrix. The key components here are hankel matrix-vector
multiplication and hankelization operator. We show that both can be computed
efficiently by the means of Fast Fourier Transform. The use of these methods
yields the reduction of the worst-case computational complexity from O(N^3) to
O(k N log(N)), where N is series length and k is the number of eigentriples
desired.Comment: 27 pages, 8 figure
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