Re: Problems with convergence ( No.1 ) |
- Date: 2012/10/22 17:01
- Name: Jan Rusz
- Dear Prof. Ozaki,
I add another observation:
After the initial 50 iterations ("scf.Mixing.StartPulay 50") the new mixing routine starts and I copy/paste here a few interations from *.DFTSCF files:
SCF= 50 NormRD= 0.029866445787 Uele= -138.011795716984 SCF= 51 NormRD= 0.029866445787 Uele= -138.011763935503 SCF= 52 NormRD= 0.136526993510 Uele= -138.009492585432 SCF= 53 NormRD= 0.136526993510 Uele= -138.011492530299 SCF= 54 NormRD= 0.085726742777 Uele= -138.006783425406 SCF= 55 NormRD= 0.085726742777 Uele= -138.011455439785 SCF= 56 NormRD= 0.140415763532 Uele= -138.005924460914 SCF= 57 NormRD= 0.140415763532 Uele= -138.011151506355 SCF= 58 NormRD= 0.150263169566 Uele= -138.018107601910 SCF= 59 NormRD= 0.150263169566 Uele= -138.011439253316
I find it curious that the "NormRD" is identical in pairs of iterations. This behavior remains until the end. Also, when the new mixing routine starts, the NormRD initially goes up quite significantly.
Right now, the system appears to converge, but very very slowly. I did similar calculations with WIEN2k MSR1 mixing routine with default parameters and it converged in 40-50 steps. While in OpenMX a single iteration is much faster (at my present computational parameters by factor of 4-5), the number of iterations needed by OpenMX are hundreds and as a result, the calculation is in fact much slower.
For our project, this is a testing calculation and we will need to deal with larger systems. Therefore we expect that OpenMX will be much faster. But we would need to understand better, how to optimize the mixing parameters.
Thank you in advance
Jan Rusz
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Re: Problems with convergence ( No.2 ) |
- Date: 2012/11/29 01:17
- Name: Kamaram <kmunira@mint.ua.edu>
- Hi,
Did you ever find a solution to your problem? I am having the same.
Kamaram
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Re: Problems with convergence ( No.3 ) |
- Date: 2012/11/30 22:54
- Name: Jan Rusz
- Hello,
unfortunately I did not. Temporarily using WIEN2k that converges for these systems very well.
Jan
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