FLEUR code plugin

Description

The FleurCalculation runs Fleur executable e.g. fleur or fleur_MPI.

Inputs

To set up an input dictionary, consider using get_inputs_fleur() which assembles input nodes in a ready-to-use single dictionary.

The table below shows all possible inputs for the FleurCalculation:

name	type	description	required
code	Code	Fleur code	yes
fleurinp	FleurinpData	Object representing inp.xml	no
parent_folder	RemoteData	Remote folder of another calculation	no
settings	Dict	special settings	no
metadata.options	Dict	computational resources	yes

fleurinp: FleurinpData, optional - Data structure which represents the inp.xml file and everything a Fleur calculation needs. For more information see FleurinpData.
parent_folder: RemoteData, optional - If specified, certain files in the previous Fleur calculation folder are copied in the new calculation folder.

Note

fleurinp and parent_folder are both optional. Depending on the setup of the inputs, one of five scenarios will happen:

fleurinp: files belonging to fleurinp will be used as input for FLEUR calculation.

fleurinp + parent_folder (FLEUR): files, given in fleurinp will be used as input for FLEUR calculation. Moreover, initial charge density will be copied from the folder of the parent calculation.

parent_folder (FLEUR): Copies inp.xml file and initial charge density from the folder of the parent FLEUR calculation.

parent_folder (input generator): Copies inp.xml file from the folder of the parent inpgen calculation.

parent_folder (input generator) + fleurinp: files belonging to fleurinp will be used as input for FLEUR calculation. Remote folder is ignored.

Outputs

The table below shows all the output nodes generated by FleurCalculation:

name	type	comment
output_parameters	Dict	contains parsed out.xml
remote_folder	FolderData	represents calculation folder
retrieved	FolderData	represents retrieved folder

All the outputs can be found in calculation.outputs.

remote_folder: RemoteData - RemoteData which represents the calculation folder on the remote machine.
retrieved: FolderData - FolderData which represents the retrieved folder on the remote machine.

output_parameters: Dict - Contains all kinds of information of the calculation and some physical quantities of the last iteration.

An example output node:

# -*- coding: utf-8 -*-
(aiidapy)% verdi data dict show 425
{
    'CalcJob_uuid': 'a6511a00-7759-484a-839d-c100dafd6118',
    'bandgap': 0.0029975592,
    'bandgap_units': 'eV',
    'charge_den_xc_den_integral': -3105.2785777045,
    'charge_density1': 3.55653e-05,
    'charge_density2': 6.70788e-05,
    'creator_name': 'fleur 27',
    'creator_target_architecture': 'GEN',
    'creator_target_structure': ' ',
    'density_convergence_units': 'me/bohr^3',
    'end_date': {
        'date': '2019/07/17',
        'time': '12:50:27'
    },
    'energy': -4405621.1469633,
    'energy_core_electrons': -99592.985569309,
    'energy_hartree': -161903.59225823,
    'energy_hartree_units': 'Htr',
    'energy_units': 'eV',
    'energy_valence_electrons': -158.7015525598,
    'fermi_energy': -0.2017877885,
    'fermi_energy_units': 'Htr',
    'force_largest': 0.0,
    'magnetic_moment_units': 'muBohr',
    'magnetic_moments': [
        2.7677822875,
        2.47601e-05,
        2.22588e-05,
        6.05518e-05,
        0.0001608849,
        0.0001504687,
        0.0001321699,
        -3.35528e-05,
        1.87169e-05,
        -0.0002957294
    ],
    'magnetic_spin_down_charges': [
        5.8532354421,
        6.7738647125,
        6.8081938915,
        6.8073232631,
        6.8162583243,
        6.8156475799,
        6.8188399492,
        6.813423175,
        6.7733972589,
        6.6797683064
    ],
    'magnetic_spin_up_charges': [
        8.6210177296,
        6.7738894726,
        6.8082161503,
        6.8073838149,
        6.8164192092,
        6.8157980486,
        6.8189721191,
        6.8133896222,
        6.7734159758,
        6.679472577
    ],
    'number_of_atom_types': 10,
    'number_of_atoms': 10,
    'number_of_iterations': 49,
    'number_of_iterations_total': 49,
    'number_of_kpoints': 240,
    'number_of_species': 1,
    'number_of_spin_components': 2,
    'number_of_symmetries': 2,
    'orbital_magnetic_moment_units': 'muBohr',
    'orbital_magnetic_moments': [],
    'orbital_magnetic_spin_down_charges': [],
    'orbital_magnetic_spin_up_charges': [],
    'output_file_version': '0.27',
    'overall_charge_density': 7.25099e-05,
    'parser_info': 'AiiDA Fleur Parser v0.2beta',
    'parser_warnings': [],
    'spin_density': 7.91911e-05,
    'start_date': {
        'date': '2019/07/17',
        'time': '10:38:24'
    },
    'sum_of_eigenvalues': -99751.687121869,
    'title': 'A Fleur input generator calulation with aiida',
    'unparsed': [],
    'walltime': 7923,
    'walltime_units': 'seconds',
    'warnings': {
        'debug': {},
        'error': {},
        'info': {},
        'warning': {}
    }
}

Errors

Errors of the parsing are reported in the log of the calculation (accessible with the verdi process report command). Everything that Fleur writes into stderr is also shown here, i.e all JuDFT error messages. Example:

(aiidapy)% verdi process report 513
*** 513 [scf: fleur run 1]: None
*** (empty scheduler output file)
*** (empty scheduler errors file)
*** 3 LOG MESSAGES:
+-> ERROR at 2019-07-17 14:57:01.108964+00:00
| parser returned exit code<302>: FLEUR calculation failed.
+-> ERROR at 2019-07-17 14:57:01.097337+00:00
| FLEUR calculation did not finishsuccessfully.
+-> WARNING at 2019-07-17 14:57:01.056220+00:00
| The following was written into std error and piped to out.error :
|  I/O warning : failed to load external entity "relax.xml"
| rm: cannot remove ‘cdn_last.hdf’: No such file or directory
| **************juDFT-Error*****************
| Error message:e>vz0
| Error occurred in subroutine:vacuz
| Hint:Vacuum energy parameter too high
| Error from PE:0/24

Moreover, all warnings and errors written by Fleur in the out.xml file are stored in the ParameterData under the key warnings, and are accessible with Calculation.res.warnings.

More serious FLEUR calculation failures generate a non-zero exit code. Each exit code has it’s own reason:

Exit code	Reason
300	One of output files can not be opened
301	No retrieved folder found
302	FLEUR calculation failed for unknown reason
303	XML output file was not found
304	Parsing of XML output file failed
305	Parsing of relax XML output file failed
310	FLEUR calculation failed due to memory issue
311	FLEUR calculation failed because atoms spilled to the vacuum
312	FLEUR calculation failed due to MT overlap
313	FLEUR calculation failed due to MT overlap during relaxation
314	Problem with cdn is suspected
315	Invalid Elements found in the LDA+U density matrix.
316	Calculation failed due to time limits.

Parallelization options

For parallel FLEUR calculations the input under metadata.options can be used. In higher level workchains this input might be present as a plain options input, but it is completely equivalent to the metadata.options input.

inputs.metadata.options = {
  'resources': {
    'num_machines': 2, #Number of computing nodes
    'num_mpiprocs_per_machine': 4, #Number of MPI processes per node
    'num_cpus_per_mpiproc': 12, #Number of OMP threads per MPI process
  },
  'withmpi': True, #This flag makes sure that the process is submitted using MPI
  'max_wallclock_seconds': 3600, #Maximum wallclock time in seconds
}

This will result in setting the following slurm Parallelization variables in the submit script.

#SBATCH --nodes=1
#SBATCH --ntasks-per-node=6
#SBATCH --cpus-per-task=8
#SBATCH --time=01:00:00
#... Further configuration options unrelated to parallelization...

'srun' '/path/to/fleur/' '<further FLEUR cmdline flags, e.g. -last_extra>'

Note, that the srun command is computer specific and is configured in verdi computer setup with the Mpirun command option.

Additional advanced features

In general see the FLEUR documentation.

While the input link with name fleurinp is used for the content of the inp.xml, additional parameters for changing the plugin behavior, can be specified in the settings input, also of type Dict.

Below we summarise some of the options that you can specify, and their effect. In each case, after having defined the content of settings_dict, you can use it as input of a calculation calc by doing:

calc.use_settings(Dict(dict=settings_dict))

Adding command-line options

If you want to add command-line options to the executable (particularly relevant e.g. ‘-hdf’ use hdf, or ‘-magma’ use different libraries, magma in this case), you can pass each option as a string in a list, as follows:

settings_dict = {
    'cmdline': ['-hdf', '-magma'],
}

The default command-line of a fleur execution of the plugin looks like this for the torque scheduler:

'mpirun' '-np' 'XX' 'path_to_fleur_executable' '-wtime' 'XXX' < 'inp.xml' > 'shell.out' 2> 'out.error'

If the code node description contains ‘hdf5’ in some form, the plugin will use per default hdf5, it will only copy the last hdf5 density back, not the full cdn.hdf file. The Fleur execution line becomes in this case:

'mpirun' '-np' 'XX' 'path_to_fleur_executable' '-last_extra' '-wtime' 'XXX' < 'inp.xml' > 'shell.out' 2> 'out.error'

Retrieving more files

AiiDA-FLEUR does not copy all output files generated by a FLEUR calculation. By default, the plugin copies only out.xml, cdn1 and inp.xml and other technical files. Depending on certain switches in used inp.xml, the plugin is capable of automatically adding additional files to the copy list:

if band=T : bands.1, bands.2

if dos=T : DOS.1, DOS.2

if pot8=T : pot*

if l_f=T : relax.xml

If you know that your calculation is producing additional files that you want to retrieve (and preserve in the AiiDA repository in the long term), you can add those files as a list as follows (here in the case of a file named testfile.txt):

settings_dict = {
  'additional_retrieve_list': ['testfile.txt'],
}

Retrieving less files

If you know that you do not want to retrieve certain files(and preserve in the AiiDA repository in the long term). i.e. the cdn1 file is to large and it is stored somewhere else anyway, you can add those files as a list as follows (here in the case of a file named testfile.txt):

settings_dict = {
  'remove_from_retrieve_list': ['testfile.txt'],
}

Copy more files remotely

The plugin copies by default the mixing_history* files if a parent_folder is given in the input.

If you know that for your calculation you need some other files on the remote machine, you can add those files as a list as follows (here in the case of a file named testfile.txt):

settings_dict = {
  'additional_remotecopy_list': ['testfile.txt'],
}

Copy less files remotely

If you know that for your calculation do not need some files which are copied per default by the plugin you can add those files as a list as follows (here in the case of a file named testfile.txt):

settings_dict = {
  'remove_from_remotecopy_list': ['testfile.txt'],
}