YamboWorkflow¶
The YamboWorkflow provides the functionality to run GW calculation from the pw-DFT step, passing in all the required
parameters for both the KS-DFT steps, scf and nscf, and the subsequent GW step. It uses the PwBaseWorkchain from aiida-quantumespresso
as a subworkflow to perform the first DFT part, if required, and the YamboRestart for the GW part. A smart logic is considered to understand what
process has to be done to achieve success. If the previous calculation is not finished_ok, the workflow will exit in a failed state: we suppose that
the success of an input calculation is guaranteed by the RestartWorkchain used at the lower level of the plugin.
Example usage.
#!/usr/bin/env runaiida
# -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import print_function
import sys
import os
from aiida.plugins import DataFactory, CalculationFactory
from aiida.orm import List, Dict
from aiida.engine import submit
from aiida_yambo.workflows.yambowf import YamboWorkflow
from aiida_quantumespresso.utils.pseudopotential import validate_and_prepare_pseudos_inputs
from ase import Atoms
import argparse
def get_options():
parser = argparse.ArgumentParser(description='YAMBO calculation.')
parser.add_argument(
'--yambocode',
type=int,
dest='yambocode_pk',
required=True,
help='The yambo(main code) codename to use')
parser.add_argument(
'--parent',
type=int,
dest='parent_pk',
required=False,
help='The parent to use')
parser.add_argument(
'--yamboprecode',
type=int,
dest='yamboprecode_pk',
required=True,
help='The precode to use')
parser.add_argument(
'--pwcode',
type=int,
dest='pwcode_pk',
required=True,
help='The pw to use')
parser.add_argument(
'--pseudo',
type=str,
dest='pseudo_family',
required=True,
help='The pseudo_family')
parser.add_argument(
'--time',
type=int,
dest='max_wallclock_seconds',
required=False,
default=30*60,
help='max wallclock in seconds')
parser.add_argument(
'--nodes',
type=int,
dest='num_machines',
required=False,
default=1,
help='number of machines')
parser.add_argument(
'--mpi',
type=int,
dest='num_mpiprocs_per_machine',
required=False,
default=1,
help='number of mpi processes per machine')
parser.add_argument(
'--threads',
type=int,
dest='num_cores_per_mpiproc',
required=False,
default=1,
help='number of threads per mpi process')
parser.add_argument(
'--queue_name',
type=str,
dest='queue_name',
required=False,
default=None,
help='queue(PBS) or partition(SLURM) name')
parser.add_argument(
'--qos',
type=str,
dest='qos',
required=False,
default=None,
help='qos name')
parser.add_argument(
'--account',
type=str,
dest='account',
required=False,
default=None,
help='account name')
args = parser.parse_args()
###### setting the machine options ######
options = {
'yambocode_pk': args.yambocode_pk,
'yamboprecode_pk': args.yamboprecode_pk,
'pwcode_pk': args.pwcode_pk,
'pseudo_family': args.pseudo_family,
'max_wallclock_seconds': args.max_wallclock_seconds,
'resources': {
"num_machines": args.num_machines,
"num_mpiprocs_per_machine": args.num_mpiprocs_per_machine,
"num_cores_per_mpiproc": args.num_cores_per_mpiproc,
},
'custom_scheduler_commands': u"export OMP_NUM_THREADS="+str(args.num_cores_per_mpiproc),
}
if args.parent_pk:
options['parent_pk']=args.parent_pk
if args.queue_name:
options['queue_name']=args.queue_name
if args.qos:
options['qos']=args.qos
if args.account:
options['account']=args.account
return options
def main(options):
###### setting the lattice structure ######
alat = 2.4955987320 # Angstrom
the_cell = [[1.000000*alat, 0.000000, 0.000000],
[-0.500000*alat, 0.866025*alat, 0.000000],
[0.000000, 0.000000, 6.4436359260]]
atoms = Atoms('BNNB', [(1.2477994910, 0.7204172280, 0.0000000000),
(-0.0000001250, 1.4408346720, 0.0000000000),
(1.2477994910, 0.7204172280, 3.2218179630),
(-0.0000001250,1.4408346720, 3.2218179630)],
cell = [1,1,1])
atoms.set_cell(the_cell, scale_atoms=False)
atoms.set_pbc([True,True,True])
StructureData = DataFactory('structure')
structure = StructureData(ase=atoms)
###### setting the kpoints mesh ######
KpointsData = DataFactory('array.kpoints')
kpoints = KpointsData()
kpoints.set_kpoints_mesh([6,6,2])
###### setting the scf parameters ######
Dict = DataFactory('dict')
params_scf = {
'CONTROL': {
'calculation': 'scf',
'verbosity': 'high',
'wf_collect': True
},
'SYSTEM': {
'ecutwfc': 130.,
'force_symmorphic': True,
'nbnd': 20
},
'ELECTRONS': {
'mixing_mode': 'plain',
'mixing_beta': 0.7,
'conv_thr': 1.e-8,
'diago_thr_init': 5.0e-6,
'diago_full_acc': True
},
}
parameter_scf = Dict(dict=params_scf)
params_nscf = {
'CONTROL': {
'calculation': 'nscf',
'verbosity': 'high',
'wf_collect': True
},
'SYSTEM': {
'ecutwfc': 130.,
'force_symmorphic': True,
'nbnd': 500
},
'ELECTRONS': {
'mixing_mode': 'plain',
'mixing_beta': 0.6,
'conv_thr': 1.e-8,
'diagonalization': 'david',
'diago_thr_init': 5.0e-6,
'diago_full_acc': True
},
}
parameter_nscf = Dict(dict=params_nscf)
KpointsData = DataFactory('array.kpoints')
kpoints = KpointsData()
kpoints.set_kpoints_mesh([6,6,2])
alat = 2.4955987320 # Angstrom
the_cell = [[1.000000*alat, 0.000000, 0.000000],
[-0.500000*alat, 0.866025*alat, 0.000000],
[0.000000, 0.000000, 6.4436359260]]
atoms = Atoms('BNNB', [(1.2477994910, 0.7204172280, 0.0000000000),
(-0.0000001250, 1.4408346720, 0.0000000000),
(1.2477994910, 0.7204172280, 3.2218179630),
(-0.0000001250,1.4408346720, 3.2218179630)],
cell = [1,1,1])
atoms.set_cell(the_cell, scale_atoms=False)
atoms.set_pbc([True,True,True])
StructureData = DataFactory('structure')
structure = StructureData(ase=atoms)
params_gw = {
'HF_and_locXC': True,
'dipoles': True,
'ppa': True,
'gw0': True,
'em1d': True,
'Chimod': 'hartree',
#'EXXRLvcs': 40,
#'EXXRLvcs_units': 'Ry',
'BndsRnXp': [1, 10],
'NGsBlkXp': 2,
'NGsBlkXp_units': 'Ry',
'GbndRnge': [1, 10],
'DysSolver': "n",
'QPkrange': [[1, 1, 8, 9]],
'DIP_CPU': "1 1 1",
'DIP_ROLEs': "k c v",
'X_CPU': "1 1 1 1",
'X_ROLEs': "q k c v",
'SE_CPU': "1 1 1",
'SE_ROLEs': "q qp b",
}
params_gw = Dict(dict=params_gw)
builder = YamboWorkflow.get_builder()
##################scf+nscf part of the builder
builder.scf.pw.structure = structure
builder.scf.pw.parameters = parameter_scf
builder.scf.kpoints = kpoints
builder.scf.pw.metadata.options.max_wallclock_seconds = \
options['max_wallclock_seconds']
builder.scf.pw.metadata.options.resources = \
dict = options['resources']
if 'queue_name' in options:
builder.scf.pw.metadata.options.queue_name = options['queue_name']
if 'qos' in options:
builder.scf.pw.metadata.options.qos = options['qos']
if 'account' in options:
builder.scf.pw.metadata.options.account = options['account']
builder.scf.pw.metadata.options.custom_scheduler_commands = options['custom_scheduler_commands']
builder.nscf.pw.structure = builder.scf.pw.structure
builder.nscf.pw.parameters = parameter_nscf
builder.nscf.kpoints = builder.scf.kpoints
builder.nscf.pw.metadata = builder.scf.pw.metadata
builder.scf.pw.code = load_node(options['pwcode_pk'])
builder.nscf.pw.code = load_node(options['pwcode_pk'])
builder.scf.pw.pseudos = validate_and_prepare_pseudos_inputs(
builder.scf.pw.structure, pseudo_family = Str(options['pseudo_family']))
builder.nscf.pw.pseudos = builder.scf.pw.pseudos
##################yambo part of the builder
builder.yres.yambo.metadata.options.max_wallclock_seconds = \
options['max_wallclock_seconds']
builder.yres.yambo.metadata.options.resources = \
dict = options['resources']
if 'queue_name' in options:
builder.yres.yambo.metadata.options.queue_name = options['queue_name']
if 'qos' in options:
builder.yres.yambo.metadata.options.qos = options['qos']
if 'account' in options:
builder.yres.yambo.metadata.options.account = options['account']
builder.yres.yambo.parameters = params_gw
builder.yres.yambo.precode_parameters = Dict(dict={})
builder.yres.yambo.settings = Dict(dict={'INITIALISE': False, 'COPY_DBS': False})
builder.yres.max_iterations = Int(5)
builder.yres.yambo.preprocessing_code = load_node(options['yamboprecode_pk'])
builder.yres.yambo.code = load_node(options['yambocode_pk'])
builder.parent_folder = load_node(options['parent_pk']).outputs.remote_folder
return builder
if __name__ == "__main__":
options = get_options()
builder = main(options)
running = submit(builder)
print("Submitted YamboWorkflow workchain; with pk=<{}>".format(running.pk))
As you may notice, here the builder has a new attributes, referring to scf, nscf and yambo parts: this means that we are actually providing the inputs for
respectively PwBaseWorkchain and YamboRestart.
The only ‘pure’ YamboWorkflow input is now the parent_folder.