[CP2K-user] Kpoints, Diagonalization algorithm and Mixing

[Lucas Lodeiro]

Hello all,

I am trying to improve the performance of MD steps for a big slab system
which contains Cu atoms... the systems has ~1500 electrons and needs 2x2x1
kpoints to compute their electronic structure (as we explore in a PW based
program, Quantum Espresso).

The first approach was to use multiple_cell 2 2 1 with just a Gamma point
and &OT method (with FULL_KINETIC preconditioner). The system is well
behaved and works fine, but the time needed for each frame is a little high
(87s per frame) to compute long MD.

As a second approach, to explore if there are a method to speed up the MD,
we use multiple_cell 1 1 1 and 2x2x1 kpoints, with standart diagonalization
algorithm with broyden mixing (attached file), but the performance is not
so good, mainly in the extrapolation step, where ASPC cannot be used. We
explore LINEAR_P, and previous P and Rho, but this does not work fine...
and needs several SCF steps to converge.
The combinations for Diagonalization algorithm and mixing are various and I
prefer to ask if there is a way to improve diagonalization based
calculations.

As the system is well behaved, is it an advantage to use another algorithm
and mixing method?
Could be a diagonalization-kpoint calculation faster than the analogous one
with OT?

Another thing is based on the kpoint scheme... We want to use a 2x2x1 gamma
centered grid... but I am not clear about MONKHORST-PACK is the Gamma
centered or displaced grid. MACDONALD and GENERAL, which are their
differences? I am familiar with the Quantum-Espresso kpoint scheme.

There are a lot of questions, sorry, but I need some insight to not search
in the fog, one by one.

Regards - Lucas Lodeiro
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