ML IERR: Difference between revisions

Revision as of 14:00, 21 November 2022

Default: ML_IERR	= 0	if ML_ISTART=2
	= 1	otherwise

Description: Calculation and output frequency of Bayesian error estimate.

Mind: This tag is only available in the development version of VASP.

This tag sets the distance in units of molecular-dynamics steps at which the Bayesian error estimates are calculated and written to the ML_LOGFILE. That is, in every ML_IERR steps an entry corresponding to the keyword BEE and/or BEEF is written. If learning is activated (ML_ISTART=0,1 or 3) Bayesian error estimation must be "on" at every molecular-dynamics step (ML_IERR=1 is required).

Only for ML_ISTART=2 the interval can be freely chosen via ML_IERR. For ML_IERR=0 the Bayesian error is never calculated (and also no corresponding log file line is written out). This is the default since for ML_ISTART=2 the Bayesian error estimation takes up a significant amount of the total calculation time.

Warning: ML_IERR>0 can be also used with the fast execution mode ML_LFAST=.TRUE., but for each step executing the Bayesian error estimation VASP switches to the slower code branch. Hence, choosing a small interval for ML_IERR will result in a considerable slowdown of the code.

@@ Line 3: / Line 3: @@
 Description: Calculation and output frequency of Bayesian error estimate.
+{{NB|mind|This tag is only available in the development version of VASP.}}
 ----
-This tag is only available in the development version of VASP.
-This tag sets the distance of molecular-dynamics steps for which the Bayesian error estimates are calculated and written to the {{TAG|ML_LOGFILE}}. This means that in every {{TAG|ML_IERR}} steps an entry corresponding to the keyword <code>BEE</code> and/or <code>BEEF</code> is written. If learning is activated ({{TAG|ML_ISTART}}=0,1 or 2) Bayesian error estimation must be "on" at every molecular-dynamics step ({{TAG|ML_IERR}}=1 is required).
+This tag sets the distance in units of molecular-dynamics steps at which the Bayesian error estimates are calculated and written to the {{TAG|ML_LOGFILE}}. That is, in every {{TAG|ML_IERR}} steps an entry corresponding to the keyword <code>BEE</code> and/or <code>BEEF</code> is written. If learning is activated ({{TAG|ML_ISTART}}=0,1 or 3) Bayesian error estimation must be "on" at every molecular-dynamics step ({{TAG|ML_IERR}}=1 is required).
-Only for {{TAG|ML_ISTART}}=2 can {{TAG|ML_IERR}} be freely chosen. For {{TAG|ML_IERR}}=0 the Bayesian error is never calculated (and also no line is written out). This is the default since for {{TAG|ML_ISTART}}=2 the Bayesian error estimation takes up a significant amount of the total calculation time.
+Only for {{TAG|ML_ISTART}}=2 the interval can be freely chosen via {{TAG|ML_IERR}}. For {{TAG|ML_IERR}}=0 the Bayesian error is never calculated (and also no corresponding log file line is written out). This is the default since for {{TAG|ML_ISTART}}=2 the Bayesian error estimation takes up a significant amount of the total calculation time.
+{{NB|warning|{{TAG|ML_IERR}}>0 can be also used with the fast execution mode {{TAG|ML_LFAST}}{{=}}.TRUE., but for each step executing the Bayesian error estimation {{VASP}} switches to the slower code branch. Hence, choosing a small interval for {{TAG|ML_IERR}} will result in a considerable slowdown of the code.}}
-{{TAG|ML_IERR}}>0 can be also used with the fast execution mode {{TAG|ML_LFAST}}=.TRUE., but at each step where the Bayesian error estimation is carried out, the code has to switch to the slow version. So choosing a too-narrow distance for {{TAG|ML_IERR}} will result in a huge slowdown of the code.
 == Related tags and articles ==