def set_up_g0w0(root_path: str):
# Material
species = ['zr', 'o']
l_max = {'zr': 6, 'o': 5}
# GW root and exciting input file
gw_root = write_input_file_with_gw_settings(
root_path, A1_gs_input,
GWInput(taskname="g0w0",
nempty=2000,
ngridq=[2, 2, 2],
skipgnd=False,
n_omega=32))
# Default basis settings
default_linear_energies = parse_lo_linear_energies(root_path +
"/groundstate")
default_los = {
'zr': DefaultLOs(default_linear_energies['zr'], energy_tol=0.8),
'o': DefaultLOs(default_linear_energies['o'], energy_tol=0.8)
}
# Default basis strings with .format tags
default_basis_string = {
'zr': parse_basis_as_string(root_path + "/groundstate/Zr.xml"),
'o': parse_basis_as_string(root_path + "/groundstate/O.xml")
}
# LO recommendation energies
lorecommendations = parse_lorecommendations(
root_path + '/lorecommendations.dat', species)
# Optimised LO energy cutoffs
energy_cutoffs = {
'zr': {
0: [60, 80, 100, 120, 140, 160, 180, 200],
1: [60, 80, 100, 120, 140, 160, 180, 200],
2: [60, 80, 100, 120, 140, 160, 180, 200],
3: [60, 80, 100, 120, 140, 160, 180, 200],
4: [60, 80, 100, 120, 140, 160, 180, 200],
5: [60, 80, 100, 120, 140, 160, 180, 200],
6: [60, 80, 100, 120, 140, 160, 180, 200]
},
'o': {
0: [60, 80, 100, 120, 140, 160, 180, 200],
1: [60, 80, 100, 120, 140, 160, 180, 200],
2: [60, 80, 100, 120, 140, 160, 180, 200],
3: [60, 80, 100, 120, 140, 160, 180, 200],
4: [60, 80, 100, 120, 140, 160, 180, 200],
5: [60, 80, 100, 120, 140, 160, 180, 200]
}
}
# Slurm script settings
env_vars = OrderedDict([
('EXE', '/users/sol/abuccheri/exciting/bin/excitingmpismp'),
('OUT', 'terminal.out')
])
module_envs = ['intel/2019']
slurm_directives = slurm.set_slurm_directives(time=[0, 23, 0, 0],
partition='all',
exclusive=True,
nodes=8,
ntasks_per_node=2,
cpus_per_task=18,
hint='nomultithread')
species_basis_string = ''
for s in species:
species_basis_string += s.capitalize() + str(l_max[s]) + '_'
for energy_cutoff in restructure_energy_cutoffs(energy_cutoffs):
# Copy groundstate directory to GW directory
max_energy_per_species = [
max(energy_per_l_channel.values())
for energy_per_l_channel in energy_cutoff.values()
]
job_dir = gw_root + '/max_energy_' + str(
int(max(max_energy_per_species)))
print(
'Creating directory, with input.xml, run.sh and optimised basis:',
job_dir)
copy_tree(root_path + '/groundstate', job_dir)
# Copy input.xml with GW settings
shutil.copy(gw_root + "/input.xml", job_dir + "/input.xml")
# New Slurm script
slurm_directives[
'job-name'] = "gw_A1_lmax_" + species_basis_string + str(
int(max(max_energy_per_species))) + 'loEcutoff'
write_file(
job_dir + '/run.sh',
slurm.set_slurm_script(slurm_directives, env_vars, module_envs))
# Write optimised basis
write_optimised_lo_basis('zr', l_max['zr'], energy_cutoff['zr'],
lorecommendations['zr'],
default_basis_string['zr'], default_los['zr'],
job_dir)
write_optimised_lo_basis('o', l_max['o'], energy_cutoff['o'],
lorecommendations['o'],
default_basis_string['o'], default_los['o'],
job_dir)
return
def input_for_lmax_pair(root_path: str, species: list, l_max: dict):
"""
Given an l_max pair, create G0W0 inputs for a specifid range of LO cut-offs per channel,
as defined in set8/basis.py
:param str root_path: Top level path to calculations
:param List[str] species: List of species
:param dict l_max: l_max associated with each species
:return:
"""
# Notes:
# Ignore queue name and have HAWK assign the correct one.
# omplace caused issues on test queue, so ignore it for now.
omp = 16
directives = set_pbs_pro_directives(time=[24, 00, 0],
nodes=1,
mpi_ranks_per_node=8,
omp_threads_per_process=omp,
cores_per_node=128,
node_type='rome',
job_name='GW_gs')
env_vars = OrderedDict([(
'EXE',
'/zhome/academic/HLRS/pri/ipralbuc/exciting-oxygen_release/bin/exciting_mpismp'
), ('OUT', 'terminal.out')])
module_envs = ['intel/19.1.0', 'mkl/19.1.0', 'impi/19.1.0']
# mpi_options = ['omplace -nt ' + str(omp)]
mpi_options = []
# Need some excessively large number for nempty => exciting takes upper bound
gw_root = write_input_file(
root_path, A1_gs_input,
GWInput(taskname="g0w0",
nempty=2000,
ngridq=[2, 2, 2],
skipgnd=False,
n_omega=32,
freqmax=1.0))
# Default basis settings
default_linear_energies = parse_lo_linear_energies(root_path +
"/groundstate")
default_los = {
'zr': DefaultLOs(default_linear_energies['zr'], energy_tol=0.8),
'o': DefaultLOs(default_linear_energies['o'], energy_tol=0.8)
}
# Default basis strings with .format tags
default_basis_string = {
'zr': parse_basis_as_string(root_path + "/groundstate/Zr.xml"),
'o': parse_basis_as_string(root_path + "/groundstate/O.xml")
}
# LO energies
lorecommendations = parse_lorecommendations(
root_path + '/lorecommendations.dat', species)
energy_cutoffs = set_lo_channel_cutoffs(l_max)
species_basis_string = "_".join(s.capitalize() + str(l_max[s])
for s in species)
for ie in range(4, 6):
energy_cutoff = energy_cutoffs[ie]
# Copy ground state directory to GW directory
job_dir = gw_root + '/max_energy_i' + str(ie)
print(
'Creating directory, with input.xml, run.sh and optimised basis:',
job_dir)
print(root_path)
copy_tree(root_path + '/groundstate', job_dir)
# Copy input.xml with GW settings
shutil.copy(gw_root + "/input.xml", job_dir + "/input.xml")
# New Slurm script
directives['N'] = "gw_A1_lmax_" + species_basis_string + str(ie)
write_file(job_dir + '/run.sh',
set_pbs_pro(directives, env_vars, module_envs, mpi_options))
# Write optimised basis
write_optimised_lo_bases(species, l_max, energy_cutoff,
lorecommendations, default_basis_string,
default_los, job_dir)