How to choose the NGRIDS in &MGRID

[huan... at mail.huji.ac.il]

Dear CP2K developers and users, 

I found a usage hint in the BASIS_MOLOPT file.
*"NGRIDS 5" (section &MGRID) will deal more efficiently (2x speedup) with 
the diffuse nature of the basis.*
Whereas in the CP2K manual, the default value of the NGRIDS is 4.

My question is that is there any rule of thumb for choosing the NGRIDS?
For example, lager basis set needs lager value of NGRIDS? 
Or how many Gaussian functions mapped on each grid would be efficient and 
accurate for the simulations?

I noticed that the CP2K website gave an example on setting the CUTOFF and 
REL_CUTOFF, https://www.cp2k.org/howto:converging_cutoff
which might related to the NGRIDS.

However, the descriptions made me confused. It might lead to another 
question.

In the introduction, it said:
If CUTOFF is *too low*, then all grids will *be coarse* and the calculation 
may become inaccurate.

While at the end of "Converging CUTOFF" section, it goes,
The reader may also notice that as CUTOFF *increases*, the number of 
Gaussians being *assigned to the* *finest grids decreases*. 

It looks like the "NG on grid 1" is the finest grid, since as the 
description of the above sentence, the number of Gaussians decreased 
significantly on grid 1.
However, this would be contrary to the introduction. Because the 
introduction indicates that the lower CUTOFF, the coarser the grid. As a 
result, the higher CUTOFF should lead to finer grid. But the example showed 
that increasing the CUTOFF pushed the Gaussian to the coarse grid.

I appreciate it if anyone could correct me if I am wrong.

Regards,
Huan
.

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