[ase-users] parallel settings

[Zhiyao Duan]

Hello everyone,
I  am just starting to use gpaw and have a problem in setting parallel parameters.my system contains 96 atoms 840 valence electrons and 720 orbitals, 2 kpts in IBZ andgrid points is  28*180*336. I was trying to run the calculation with 48 cores using the following script:
import numpy as npfrom ase import Atomsfrom gpaw import GPAW, PW, FermiDirac, MethfesselPaxtonfrom ase.optimize import FIRE,BFGS
np.seterr(under="ignore")
model=read('au_tio2.vasp',format='vasp')
calc = GPAW(xc='PBE',            mode='pw',            kpts=(4, 1, 1),            random=True,            eigensolver='rmm-diis',            txt='au_tio2_relax.txt')
model.set_calculator(calc)opt = BFGS(model)opt.run(0.05)
write('final_relax.vasp',model, format='vasp',direct=True)
the job can run normally but much slower than vasp with similar setups.I thought the slowness is due to parallelization, so I add parallel={'band':4} to divide bands to 4 groups. This time the job failed witherror:
File "/usr/local/gpaw/lib/python/gpaw/mpi/__init__.py", line 939, in autofinalize    raise RuntimeError('All the CPUs must be used')RuntimeError: All the CPUs must be used
can anybody help me figuring out why this happens?
Another question is how to compare the speed of gpaw and vasp?As I mentioned above, on my system vasp seems much faster, maybe this is due to number of valence electrons included in the calculation? In my case, Ti atom has 12 valence electrons in gpaw comparing to 4 in vasp. Or the better performance of vasp isdue to some other factors like parallelization?
Thank you guys!
Zhiyao 		 	   		  
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