<li><ahref="gpaw/benchmark/A_carbon-nanotube/input.py">Test Case A</a>
<li><ahref="gpaw/benchmark/B_copper-filament/input.py">Test Case B</a>
<li><ahref="gpaw/benchmark/C_silicon-cluster/input.py">Test Case C</a>
</ul>
</td>
<td>132,000</td>
...
...
@@ -362,27 +367,6 @@ The code can be used for plain Newtonian dynamics, or for cosmological integrati
-[Build & run instructions, details about the benchmarks](./gadget/4.0/README.md)
# GPAW <a name="gpaw"></a>
GPAW is an efficient program package for electronic structure calculations based on the density functional theory (DFT) and the time-dependent density functional theory (TD-DFT). The density-functional theory allows studies of ground state properties such as energetics and equilibrium geometries, while the time-dependent density functional theory can be used for calculating excited state properties such as optical spectra. The program package includes two complementary implementations of time-dependent density functional theory: a linear response formalism and a time-propagation in real time.
The program uses the projector augmented wave (PAW) method that allows one to get rid of the core electrons and work with soft pseudo valence wave functions. The PAW method can be applied on the same footing to all elements, for example, it provides a reliable description of the transition metal elements and the first row elements with open p-shells that are often problematic for standard pseudopotentials. A further advantage of the PAW method is that it is an all-electron method (frozen core approximation) and there is a one to one transformation between the pseudo and all-electron quantities.
The equations of the (time-dependent) density functional theory within the PAW method are discretized using finite-differences and uniform real-space grids. The real-space representation allows flexible boundary conditions, as the system can be finite or periodic in one, two or three dimensions (e.g. cluster, slab, bulk). The accuracy of the discretization is controlled basically by single parameter, the grid spacing. The real-space representation allows also efficient parallelization with domain decomposition.
The program offers several parallelization levels. The most basic parallelization strategy is domain decomposition over the real-space grid. In magnetic systems it is possible to parallelize over spin, and in systems that have k-points (surfaces or bulk systems) parallelization over k-points is also possible. Furthermore, parallelization over electronic states is possible in DFT and in real-time TD-DFT calculations. GPAW is written in Python and C and parallelized with MPI.
- Web site: https://wiki.fysik.dtu.dk/gpaw/
- Code download: [gpaw GitLab repository](https://gitlab.com/gpaw/gpaw) or [gpaw on
PyPi](https://pypi.org/project/gpaw/)
- Build instructions: [gpaw README, section "Mechanics of building the benchmark"](gpaw/README.md#mechanics-of-building-the-benchmark)
[gpaw README, section "Mechanics of running the benchmark"](gpaw/README.md#mechanics-of-running-the-benchmark)
# GROMACS <a name="gromacs"></a>
GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles.
