GPAW Convergence Behavior
A talk given by Ansgar Schaefer studying convergence behaviour for rutiles is here (pdf).
General suggestions for helping GPAW convergence are here.
A discussion and suggestions for converging some simple systems can be found here.
Other convergence experience:
System | Who | Action |
---|---|---|
Graphene with vacancy | Felix/JensH | Increase Fermi Temp from 0.1 to 0.2, use cg |
Graphene with vacancy | cpo | change nbands from -10 to -20, MixerDif(beta=0.03, nmaxold=5, weight=50.0) |
Enzyme for CO2 reduction | grabow | use Davidson solver (faster as well?) |
GPAW Memory Estimation
The get a guess for the right number of nodes to run on for GPAW, run the
following line interactively:
Code Block |
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gpaw-python <yourjob>.py --dry-run=<numberofnodes>
(e.g. gpaw-python graphene.py --dry-run=16)
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Number of nodes should be a multiple of 8. This will run quickly
(because it doesn't do the calculation). Then check that the
following number is <3GiB:
Code Block |
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Memory estimate
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Calculator 574.32 MiB
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