faster convergence by restarting with WAVECAR?
Posted: Mon Mar 14, 2011 7:35 am
Hi,
I accidentally found that for my LDA+U calculations with slow convergence, it is actually easier to reach convergence by breaking up the calculation into two steps,
1) Starting from scratch, limiting NELM to say 12 with default NELMDL= -5. 12 electronic steps are not enough to fully converge.
2) Read the CHGCAR and WAVECAR from step 1 with normal NELM (e.g. 20) and no other change.
This actually works much better than a one-step approach, also starting from scratch of course; the latter often fails to reach convergence at all even after many (>50) number of steps. All tests were done with ALGO=normal (works better than fast).
Sorry if this is a repost. I did not find anything related in the manual or in the forum. My question is, why would breaking up the calculation help? Something to do with the iterative nature of diagonalization algorithm? And is there any setting to change so that a single step can obtain similar results? I tried the suggestion about the mixing parameters, and found no obvious improvement.
Best regards,
Fei
I accidentally found that for my LDA+U calculations with slow convergence, it is actually easier to reach convergence by breaking up the calculation into two steps,
1) Starting from scratch, limiting NELM to say 12 with default NELMDL= -5. 12 electronic steps are not enough to fully converge.
2) Read the CHGCAR and WAVECAR from step 1 with normal NELM (e.g. 20) and no other change.
This actually works much better than a one-step approach, also starting from scratch of course; the latter often fails to reach convergence at all even after many (>50) number of steps. All tests were done with ALGO=normal (works better than fast).
Sorry if this is a repost. I did not find anything related in the manual or in the forum. My question is, why would breaking up the calculation help? Something to do with the iterative nature of diagonalization algorithm? And is there any setting to change so that a single step can obtain similar results? I tried the suggestion about the mixing parameters, and found no obvious improvement.
Best regards,
Fei