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) |
Nitrogenase FeVCo for CO2 reduction |
grabow |
use Davidson solver (faster as well?), although later jvarley said MixerSum |
Several surfaces |
aap |
Broyden mixer with Beta=0.5 |
GPAW Memory Estimation
The get a guess for the right number of nodes to run on for GPAW, run the
following line interactively:
gpaw-python <yourjob>.py --dry-run=<numberofnodes> (e.g. gpaw-python graphene.py --dry-run=16)
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 <3GB for the 8-core farm, <4GB for the 12-core farm:
Memory estimate --------------- Calculator 574.32 MiB
Building a Private Version of GPAW
- Use svn to check out the version of GPAW that you want to use
- copy /afs/slac/g/suncat/bin/privgpaw.csh into whatever directory you like
- edit the two variables GPAW_BASE ("base" GPAW release that you want to re-use for numpy, mpi etc.) and GPAW_HOME (directory where you checked out GPAW)
- Use the commands:
privgpaw.csh build privgpaw.csh test privgpaw.csh bsub <arguments>
Some notes:
- You can see a list of available installed versions here (to use for GPAW_BASE).
- The syntax for the "bsub" option is identical to the gpaw-bsub command described here.
- The above assumes that the base release is compatible with your checked out GPAW version. Talk to cpo if you have questions about this.
- The above doesn't include support for a private version of ASE. When that becomes important we will add it.
Jacapo Parallel NEB Example
You can find a Jacapo parallel NEB example here. Some lines need to change for a restart. An example is here.
Some important notes:
- the number of processors selected for a parallel NEB must be an integer multiple of the NumberOfImages-2 (the images at the end points are "fixed").
- Parallel NEB settings (e.g. number of cores) can be debugged running in the suncat-test queue with 1 processor per non-fixed image.
- this restart example turns on the "FIRE" and and "climb" parameters: this is for later in the calculation. The documentation here discusses the reasons for that (although perhaps doesn't spell out clearly what the criteria are for turning those on).