def __init__(self):
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg('groupname', 'str', 'The name of the group of simulations you want to submit. If none is given, '
'a randomly generated string will be used instead.', None, val.String())
self._arg('datadir', 'str', 'The directory in which to retrieve your results.', None, val.String())
self._arg('verbose', 'bool', 'Turn verbosity mode on or off.', False, val.Boolean())
self._cloud = None
def __init__(self, _configapp=None):
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg('jobname', 'str', 'Job name (identifier)', None, val.String())
self._arg('queue', 'str', 'The queue to run on', self._defaults['queue'], val.String())
self._arg('app', 'str', 'The application profile', self._defaults['app'], val.String())
self._arg('ngpu', 'int', 'Number of GPUs to use for a single job', self._defaults['ngpu'],
val.Number(int, '0POS'))
self._arg('ncpu', 'int', 'Number of CPUs to use for a single job', self._defaults['ncpu'],
val.Number(int, '0POS'))
self._arg('memory', 'int', 'Amount of memory per job (MB)', self._defaults['memory'], val.Number(int, '0POS'))
self._arg('walltime', 'int', 'Job timeout (hour:min or min)', self._defaults['walltime'], val.Number(int, '0POS'))
self._arg('resources', 'list', 'Resources of the queue', self._defaults['resources'], val.String(), nargs='*')
self._arg('environment', 'list', 'Things to run before the job (sourcing envs).', self._defaults['environment'],
val.String(), nargs='*')
self._arg('outputstream', 'str', 'Output stream.', 'lsf.%J.out', val.String())
self._arg('errorstream', 'str', 'Error stream.', 'lsf.%J.err', val.String())
self._arg('datadir', 'str', 'The path in which to store completed trajectories.', None, val.String())
self._arg('trajext', 'str', 'Extension of trajectory files. This is needed to copy them to datadir.', 'xtc', val.String())
# Load LSF configuration profile
lsfconfig = _config['lsf']
profile = None
if _configapp is not None:
if lsfconfig is not None:
if os.path.isfile(lsfconfig) and lsfconfig.endswith(('.yml', '.yaml')):
try:
with open(lsfconfig, 'r') as f:
profile = yaml.load(f)
logger.info('Loaded LSF configuration YAML file {}'.format(lsfconfig))
except:
logger.warning('Could not load YAML file {}'.format(lsfconfig))
else:
logger.warning('{} does not exist or it is not a YAML file.'.format(lsfconfig))
if profile:
try:
properties = profile[_configapp]
except:
raise RuntimeError('There is no profile in {} for configuration '
'app {}'.format(lsfconfig, _configapp))
for p in properties:
self.__dict__[p] = properties[p]
logger.info('Setting {} to {}'.format(p, properties[p]))
else:
raise RuntimeError('No LSF configuration YAML file defined for the configapp')
else:
if lsfconfig is not None:
logger.warning('LSF configuration YAML file defined without configuration app')
# Find executables
self._qsubmit = LsfQueue._find_binary('bsub')
self._qinfo = LsfQueue._find_binary('bqueues')
self._qcancel = LsfQueue._find_binary('bkill')
self._qstatus = LsfQueue._find_binary('bjobs')
def __init__(self):
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg('datadir', 'str', 'The path in which to store completed trajectories.', None, val.String())
self._arg('trajext', 'str', 'Extension of trajectory files. This is needed to copy them to datadir.', 'xtc',
val.String())
self._arg('copy', 'list', 'A list of file names or globs for the files to copy to datadir', ('*.xtc', ),
val.String(), nargs='*')
self._cmdDeprecated('trajext', 'copy')
self._states = dict()
self._queue = None
self._shutdown = False
def __init__(self):
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg(
'groupname', 'str',
'The name of the group of simulations you want to submit. If none is given, '
'a randomly generated string will be used instead.', None,
val.String())
self._arg('datadir', 'str',
'The directory in which to retrieve your results.', None,
val.String())
self._arg('verbose', 'bool', 'Turn verbosity mode on or off.', False,
val.Boolean())
self._cloud = None
def __init__(self):
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg('groupname', 'str', 'The name of the group of simulations you want to submit. If none is given, '
'a randomly generated string will be used instead.', None, val.String())
self._arg('datadir', 'str', 'The directory in which to retrieve your results.', None, val.String())
self._arg('instancetype', 'str', 'Instance type', 'g2.2xlarge', val.String(), valid_values=('g2.2xlarge', 'r4.large', 'p2.xlarge'))
self._arg('hashnames', 'bool', 'If True, each job will have a name created from the hash of its directory '
'instead of using the directory name.', False, val.Boolean())
self._arg('verbose', 'bool', 'Turn verbosity mode on or off.', False, val.Boolean())
self._arg('ngpu', 'int', 'Number of GPUs to use for a single job', 0, val.Number(int, '0POS'))
self._arg('ncpu', 'int', 'Number of CPUs to use for a single job', 1, val.Number(int, '0POS'))
self._arg('memory', 'int', 'Amount of memory per job (MB)', 8000, val.Number(int, '0POS'))
self._cloud = None
def __init__(self):
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg('jobname', 'str', 'Job name (identifier)', None,
val.String())
self._arg('queue', 'str', 'The queue to run on',
self._defaults[self._defaults['default_queue']],
val.String())
self._arg('ngpu', 'int', 'Number of GPUs to use for a single job',
self._defaults['ngpu'], val.Number(int, '0POS'))
self._arg('ncpu', 'int', 'Number of CPUs to use for a single job',
self._defaults['ncpu'], val.Number(int, '0POS'))
self._arg('memory', 'int', 'Amount of memory per job (MB)',
self._defaults['memory'], val.Number(int, '0POS'))
self._arg('walltime', 'int', 'Job timeout (hour:min or min)',
self._defaults['walltime'], val.Number(int, '0POS'))
self._arg('resources',
'list',
'Resources of the queue',
self._defaults['resources'],
val.String(),
nargs='*')
self._arg('environment',
'list',
'Things to run before the job (sourcing envs).',
self._defaults['environment'],
val.String(),
nargs='*')
self._arg('outputstream', 'str', 'Output stream.', 'lsf.%J.out',
val.String())
self._arg('errorstream', 'str', 'Error stream.', 'lsf.%J.err',
val.String())
self._arg('datadir', 'str',
'The path in which to store completed trajectories.', None,
val.String())
self._arg(
'trajext', 'str',
'Extension of trajectory files. This is needed to copy them to datadir.',
'xtc', val.String())
# Find executables
self._qsubmit = LsfQueue._find_binary('bsub')
self._qinfo = LsfQueue._find_binary('bqueues')
self._qcancel = LsfQueue._find_binary('bkill')
self._qstatus = LsfQueue._find_binary('bjobs')
def __init__(self):
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg('datadir', 'str',
'The path in which to store completed trajectories.', None,
val.String())
self._arg(
'trajext', 'str',
'Extension of trajectory files. This is needed to copy them to datadir.',
'xtc', val.String())
self._arg(
'copy',
'list',
'A list of file names or globs for the files to copy to datadir',
('*.xtc', ),
val.String(),
nargs='*')
self._cmdDeprecated('trajext', 'copy')
self._states = dict()
self._queue = None
self._shutdown = False
def __init__(self, _configapp=None):
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg('version',
'int',
'LSF major version',
self._defaults['version'],
valid_values=[9, 10])
self._arg('jobname', 'str', 'Job name (identifier)', None,
val.String())
self._arg(
'queue',
'list',
'The queue or list of queues to run on. If list, it attempts to submit the job to '
'the first queue listed',
self._defaults['queue'],
val.String(),
nargs='*')
self._arg('app', 'str', 'The application profile',
self._defaults['app'], val.String())
self._arg('ngpu', 'int', 'Number of GPUs to use for a single job',
self._defaults['ngpu'], val.Number(int, '0POS'))
self._arg(
'gpu_options', 'dict', 'Number of GPUs to use for a single job',
self._defaults['gpu_options'],
val.Dictionary(key_type=str,
valid_keys=['mode', 'mps', 'j_exclusive'],
value_type={
'mode': str,
'mps': str,
'j_exclusive': str
},
valid_values={
'mode': ['shared', 'exclusive_process'],
'mps': ['yes', 'no'],
'j_exclusive': ['yes', 'no']
}))
self._arg('ncpu', 'int', 'Number of CPUs to use for a single job',
self._defaults['ncpu'], val.Number(int, '0POS'))
self._arg('memory', 'int', 'Amount of memory per job (MiB)',
self._defaults['memory'], val.Number(int, '0POS'))
self._arg('walltime', 'int', 'Job timeout (hour:min or min)',
self._defaults['walltime'], val.Number(int, '0POS'))
self._arg('resources',
'list',
'Resources of the queue',
self._defaults['resources'],
val.String(),
nargs='*')
self._cmdDeprecated('environment', 'prerun')
self._arg('outputstream', 'str', 'Output stream.', 'lsf.%J.out',
val.String())
self._arg('errorstream', 'str', 'Error stream.', 'lsf.%J.err',
val.String())
self._arg('datadir', 'str',
'The path in which to store completed trajectories.', None,
val.String())
self._arg(
'trajext', 'str',
'Extension of trajectory files. This is needed to copy them to datadir.',
'xtc', val.String())
self._arg(
'envvars', 'str',
'Envvars to propagate from submission node to the running node (comma-separated)',
self._defaults['envvars'], val.String())
self._arg(
'prerun',
'list',
'Shell commands to execute on the running node before the job (e.g. '
'loading modules)',
self._defaults['prerun'],
val.String(),
nargs='*')
# Load LSF configuration profile
lsfconfig = _config['lsf']
profile = None
if _configapp is not None:
if lsfconfig is not None:
if os.path.isfile(lsfconfig) and lsfconfig.endswith(
('.yml', '.yaml')):
try:
with open(lsfconfig, 'r') as f:
profile = yaml.load(f)
logger.info(
'Loaded LSF configuration YAML file {}'.format(
lsfconfig))
except:
logger.warning(
'Could not load YAML file {}'.format(lsfconfig))
else:
logger.warning(
'{} does not exist or it is not a YAML file.'.format(
lsfconfig))
if profile:
try:
properties = profile[_configapp]
except:
raise RuntimeError(
'There is no profile in {} for configuration '
'app {}'.format(lsfconfig, _configapp))
for p in properties:
self.__dict__[p] = properties[p]
logger.info('Setting {} to {}'.format(
p, properties[p]))
else:
raise RuntimeError(
'No LSF configuration YAML file defined for the configapp')
else:
if lsfconfig is not None:
logger.warning(
'LSF configuration YAML file defined without configuration app'
)
# Find executables
self._qsubmit = LsfQueue._find_binary('bsub')
self._qinfo = LsfQueue._find_binary('bqueues')
self._qcancel = LsfQueue._find_binary('bkill')
self._qstatus = LsfQueue._find_binary('bjobs')
def __init__(
self, _configapp=None, _configfile=None, _findExecutables=True, _logger=True
):
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg("jobname", "str", "Job name (identifier)", None, val.String())
self._arg(
"partition",
"str",
"The queue (partition) or list of queues to run on. If list, the one offering "
"earliest initiation will be used.",
self._defaults["partition"],
val.String(),
nargs="*",
)
self._arg(
"priority", "str", "Job priority", self._defaults["priority"], val.String()
)
self._arg(
"ngpu",
"int",
"Number of GPUs to use for a single job",
self._defaults["ngpu"],
val.Number(int, "0POS"),
)
self._arg(
"ncpu",
"int",
"Number of CPUs to use for a single job",
self._defaults["ncpu"],
val.Number(int, "POS"),
)
self._arg(
"memory",
"int",
"Amount of memory per job (MiB)",
self._defaults["memory"],
val.Number(int, "POS"),
)
self._arg(
"gpumemory",
"int",
"Only run on GPUs with at least this much memory. Needs special setup of SLURM. "
"Check how to define gpu_mem on SLURM.",
None,
val.Number(int, "0POS"),
)
self._arg(
"walltime",
"int",
"Job timeout (minutes)",
self._defaults["walltime"],
val.Number(int, "POS"),
)
self._cmdDeprecated("environment", "envvars")
self._arg(
"mailtype",
"str",
"When to send emails. Separate options with commas like 'END,FAIL'.",
None,
val.String(),
)
self._arg("mailuser", "str", "User email address.", None, val.String())
self._arg(
"outputstream", "str", "Output stream.", "slurm.%N.%j.out", val.String()
)
self._arg(
"errorstream", "str", "Error stream.", "slurm.%N.%j.err"
), val.String()
self._arg(
"datadir",
"str",
"The path in which to store completed trajectories.",
None,
val.String(),
)
self._arg(
"trajext",
"str",
"Extension of trajectory files. This is needed to copy them to datadir.",
"xtc",
val.String(),
)
self._arg(
"nodelist",
"list",
"A list of nodes on which to run every job at the *same time*! Careful! The jobs"
" will be duplicated!",
None,
val.String(),
nargs="*",
)
self._arg(
"exclude",
"list",
"A list of nodes on which *not* to run the jobs. Use this to select nodes on "
"which to allow the jobs to run on.",
None,
val.String(),
nargs="*",
)
self._arg(
"envvars",
"str",
"Envvars to propagate from submission node to the running node (comma-separated)",
self._defaults["envvars"],
val.String(),
)
self._arg(
"prerun",
"list",
"Shell commands to execute on the running node before the job (e.g. "
"loading modules)",
self._defaults["prerun"],
val.String(),
nargs="*",
)
self._arg(
"account",
"str",
"Charge resources used by the jobs to specified account.",
None,
val.String(),
)
self._arg(
"user",
"str",
"The SLURM user submitting and managing jobs",
getpass.getuser(),
val.String(),
)
# Load Slurm configuration profile
loadConfig(self, "slurm", _configfile, _configapp, _logger)
# Find executables
if _findExecutables:
self._qsubmit = SlurmQueue._find_binary("sbatch")
self._qinfo = SlurmQueue._find_binary("sinfo")
self._qcancel = SlurmQueue._find_binary("scancel")
self._qstatus = SlurmQueue._find_binary("squeue")
self._qjobinfo = SlurmQueue._find_binary("sacct")
self._checkQueue()
def __init__(self):
"""
Call super constructor and initialise with name.
"""
ProtocolInterface.__init__(self, "tcpsocket")
def __init__(self):
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg('jobname', 'str', 'Job name (identifier)', None,
val.String())
self._arg('partition', 'str', 'The queue (partition) to run on',
self._defaults[self._defaults['default_partition']],
val.String())
self._arg('priority', 'str', 'Job priority',
self._defaults['priority'], val.String())
self._arg('ngpu', 'int', 'Number of GPUs to use for a single job',
self._defaults['ngpu'], val.Number(int, '0POS'))
self._arg('ncpu', 'int', 'Number of CPUs to use for a single job',
self._defaults['ncpu'], val.Number(int, 'POS'))
self._arg('memory', 'int', 'Amount of memory per job (MB)',
self._defaults['memory'], val.Number(int, 'POS'))
self._arg(
'gpumemory', 'int',
'Only run on GPUs with at least this much memory. Needs special setup of SLURM. '
'Check how to define gpu_mem on SLURM.', None,
val.Number(int, '0POS'))
self._arg('walltime', 'int', 'Job timeout (s)',
self._defaults['walltime'], val.Number(int, 'POS'))
self._arg('environment', 'str', 'Envvars to propagate to the job.',
self._defaults['environment'], val.String())
self._arg(
'mailtype', 'str',
'When to send emails. Separate options with commas like \'END,FAIL\'.',
None, val.String())
self._arg('mailuser', 'str', 'User email address.', None, val.String())
self._arg('outputstream', 'str', 'Output stream.', 'slurm.%N.%j.out',
val.String())
self._arg(
'errorstream', 'str', 'Error stream.',
'slurm.%N.%j.err'), val.String() # Maybe change these to job name
self._arg('datadir', 'str',
'The path in which to store completed trajectories.', None,
val.String())
self._arg(
'trajext', 'str',
'Extension of trajectory files. This is needed to copy them to datadir.',
'xtc', val.String())
self._arg(
'nodelist',
'list',
'A list of nodes on which to run every job at the *same time*! Careful! The jobs'
' will be duplicated!',
None,
val.String(),
nargs='*')
self._arg(
'exclude',
'list',
'A list of nodes on which *not* to run the jobs. Use this to select nodes on '
'which to allow the jobs to run on.',
None,
val.String(),
nargs='*')
# Find executables
self._qsubmit = SlurmQueue._find_binary('sbatch')
self._qinfo = SlurmQueue._find_binary('sinfo')
self._qcancel = SlurmQueue._find_binary('scancel')
self._qstatus = SlurmQueue._find_binary('squeue')
def __init__(self,
_configapp=None,
_configfile=None,
_findExecutables=True,
_logger=True):
from playmolecule import Session, Job
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg(
"parentjob",
"playmolecule.job.Job",
"Spawn all jobs as children of this job",
default=None,
required=False,
validator=val.Object(Job),
)
self._arg(
"session",
"playmolecule.session.Session",
"The current PMWS Session object",
required=True,
validator=val.Object(Session),
)
self._arg("jobname", "str", "Job name (identifier)", None,
val.String())
self._arg("group", "str", "Group name (identifier)", None,
val.String())
self._arg(
"ngpu",
"int",
"Number of GPUs",
default=0,
validator=val.Number(int, "0POS"),
)
self._arg(
"ncpu",
"int",
"Number of CPUs",
default=1,
validator=val.Number(int, "0POS"),
)
self._arg(
"memory",
"int",
"Amount of memory (MB)",
default=1000,
validator=val.Number(int, "POS"),
)
self._arg("app",
"str",
"App name",
required=True,
validator=val.String())
self._arg(
"configname",
"str",
"Name of the file containing the individual job configurations yaml or json. Not a filepath, just the name. All submitted folders must contain this file.",
None,
val.String(),
)
self._arg(
"retrievedir",
"str",
"Directory in which to retrieve the results of jobs",
None,
val.String(),
)
self._arg(
"datadir",
"str",
"Directory in which to copy or symlink the output directory.",
None,
val.String(),
)
self._arg(
"symlink",
"bool",
"Set to False to copy instead of symlink the directories from the retrievedir to datadir",
True,
val.Boolean(),
)
self._arg(
"copy",
"list",
"A list of file names or globs for the files to copy or symlink from retrievedir to datadir.",
("/", ),
val.String(),
nargs="*",
)
loadConfig(self, "playmolecule", _configfile, _configapp, _logger)
def __init__(self, _configapp=None):
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg('jobname', 'str', 'Job name (identifier)', None,
val.String())
self._arg(
'partition',
'str',
'The queue (partition) or list of queues to run on. If list, the one offering '
'earliest initiation will be used.',
self._defaults['partition'],
val.String(),
nargs='*')
self._arg('priority', 'str', 'Job priority',
self._defaults['priority'], val.String())
self._arg('ngpu', 'int', 'Number of GPUs to use for a single job',
self._defaults['ngpu'], val.Number(int, '0POS'))
self._arg('ncpu', 'int', 'Number of CPUs to use for a single job',
self._defaults['ncpu'], val.Number(int, 'POS'))
self._arg('memory', 'int', 'Amount of memory per job (MiB)',
self._defaults['memory'], val.Number(int, 'POS'))
self._arg(
'gpumemory', 'int',
'Only run on GPUs with at least this much memory. Needs special setup of SLURM. '
'Check how to define gpu_mem on SLURM.', None,
val.Number(int, '0POS'))
self._arg('walltime', 'int', 'Job timeout (minutes)',
self._defaults['walltime'], val.Number(int, 'POS'))
self._cmdDeprecated('environment', 'envvars')
self._arg(
'mailtype', 'str',
'When to send emails. Separate options with commas like \'END,FAIL\'.',
None, val.String())
self._arg('mailuser', 'str', 'User email address.', None, val.String())
self._arg('outputstream', 'str', 'Output stream.', 'slurm.%N.%j.out',
val.String())
self._arg('errorstream', 'str', 'Error stream.',
'slurm.%N.%j.err'), val.String()
self._arg('datadir', 'str',
'The path in which to store completed trajectories.', None,
val.String())
self._arg(
'trajext', 'str',
'Extension of trajectory files. This is needed to copy them to datadir.',
'xtc', val.String())
self._arg(
'nodelist',
'list',
'A list of nodes on which to run every job at the *same time*! Careful! The jobs'
' will be duplicated!',
None,
val.String(),
nargs='*')
self._arg(
'exclude',
'list',
'A list of nodes on which *not* to run the jobs. Use this to select nodes on '
'which to allow the jobs to run on.',
None,
val.String(),
nargs='*')
self._arg(
'envvars', 'str',
'Envvars to propagate from submission node to the running node (comma-separated)',
self._defaults['envvars'], val.String())
self._arg(
'prerun',
'list',
'Shell commands to execute on the running node before the job (e.g. '
'loading modules)',
self._defaults['prerun'],
val.String(),
nargs='*')
self._arg('account', 'str',
'Charge resources used by the jobs to specified account.',
None, val.String())
# Load Slurm configuration profile
slurmconfig = _config['slurm']
profile = None
if _configapp is not None:
if slurmconfig is not None:
if os.path.isfile(slurmconfig) and slurmconfig.endswith(
('.yml', '.yaml')):
try:
with open(slurmconfig, 'r') as f:
profile = yaml.load(f)
logger.info(
'Loaded Slurm configuration YAML file {}'.format(
slurmconfig))
except:
logger.warning(
'Could not load YAML file {}'.format(slurmconfig))
else:
logger.warning(
'{} does not exist or it is not a YAML file.'.format(
slurmconfig))
if profile:
try:
properties = profile[_configapp]
except:
raise RuntimeError(
'There is no profile in {} for configuration '
'app {}'.format(slurmconfig, _configapp))
for p in properties:
setattr(self, p, properties[p])
logger.info('Setting {} to {}'.format(
p, properties[p]))
else:
raise RuntimeError(
'No Slurm configuration YAML file defined for the configapp'
)
else:
if slurmconfig is not None:
logger.warning(
'Slurm configuration YAML file defined without configuration app'
)
# Find executables
self._qsubmit = SlurmQueue._find_binary('sbatch')
self._qinfo = SlurmQueue._find_binary('sinfo')
self._qcancel = SlurmQueue._find_binary('scancel')
self._qstatus = SlurmQueue._find_binary('squeue')
def __init__(self, _configapp=None):
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg('version', 'int', 'LSF major version', self._defaults['version'], valid_values=[9, 10])
self._arg('jobname', 'str', 'Job name (identifier)', None, val.String())
self._arg('queue', 'list', 'The queue or list of queues to run on. If list, it attempts to submit the job to '
'the first queue listed', self._defaults['queue'], val.String(), nargs='*')
self._arg('app', 'str', 'The application profile', self._defaults['app'], val.String())
self._arg('ngpu', 'int', 'Number of GPUs to use for a single job', self._defaults['ngpu'],
val.Number(int, '0POS'))
self._arg('gpu_options', 'dict', 'Number of GPUs to use for a single job', self._defaults['gpu_options'],
val.Dictionary(key_type=str, valid_keys=['mode', 'mps', 'j_exclusive'],
value_type={'mode': str, 'mps': str, 'j_exclusive': str},
valid_values={'mode': ['shared', 'exclusive_process'],
'mps': ['yes', 'no'], 'j_exclusive': ['yes', 'no']}
)
)
self._arg('ncpu', 'int', 'Number of CPUs to use for a single job', self._defaults['ncpu'],
val.Number(int, '0POS'))
self._arg('memory', 'int', 'Amount of memory per job (MiB)', self._defaults['memory'], val.Number(int, '0POS'))
self._arg('walltime', 'int', 'Job timeout (hour:min or min)', self._defaults['walltime'],
val.Number(int, '0POS'))
self._arg('resources', 'list', 'Resources of the queue', self._defaults['resources'], val.String(), nargs='*')
self._cmdDeprecated('environment', 'prerun')
self._arg('outputstream', 'str', 'Output stream.', 'lsf.%J.out', val.String())
self._arg('errorstream', 'str', 'Error stream.', 'lsf.%J.err', val.String())
self._arg('datadir', 'str', 'The path in which to store completed trajectories.', None, val.String())
self._arg('trajext', 'str', 'Extension of trajectory files. This is needed to copy them to datadir.', 'xtc',
val.String())
self._arg('envvars', 'str', 'Envvars to propagate from submission node to the running node (comma-separated)',
self._defaults['envvars'], val.String())
self._arg('prerun', 'list', 'Shell commands to execute on the running node before the job (e.g. '
'loading modules)', self._defaults['prerun'], val.String(), nargs='*')
# Load LSF configuration profile
lsfconfig = _config['lsf']
profile = None
if _configapp is not None:
if lsfconfig is not None:
if os.path.isfile(lsfconfig) and lsfconfig.endswith(('.yml', '.yaml')):
try:
with open(lsfconfig, 'r') as f:
profile = yaml.load(f)
logger.info('Loaded LSF configuration YAML file {}'.format(lsfconfig))
except:
logger.warning('Could not load YAML file {}'.format(lsfconfig))
else:
logger.warning('{} does not exist or it is not a YAML file.'.format(lsfconfig))
if profile:
try:
properties = profile[_configapp]
except:
raise RuntimeError('There is no profile in {} for configuration '
'app {}'.format(lsfconfig, _configapp))
for p in properties:
self.__dict__[p] = properties[p]
logger.info('Setting {} to {}'.format(p, properties[p]))
else:
raise RuntimeError('No LSF configuration YAML file defined for the configapp')
else:
if lsfconfig is not None:
logger.warning('LSF configuration YAML file defined without configuration app')
# Find executables
self._qsubmit = LsfQueue._find_binary('bsub')
self._qinfo = LsfQueue._find_binary('bqueues')
self._qcancel = LsfQueue._find_binary('bkill')
self._qstatus = LsfQueue._find_binary('bjobs')
def __init__(self, _configapp=None):
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg('jobname', 'str', 'Job name (identifier)', None, val.String())
self._arg('partition', 'str', 'The queue (partition) to run on', self._defaults['partition'], val.String())
self._arg('priority', 'str', 'Job priority', self._defaults['priority'], val.String())
self._arg('ngpu', 'int', 'Number of GPUs to use for a single job', self._defaults['ngpu'],
val.Number(int, '0POS'))
self._arg('ncpu', 'int', 'Number of CPUs to use for a single job', self._defaults['ncpu'],
val.Number(int, 'POS'))
self._arg('memory', 'int', 'Amount of memory per job (MB)', self._defaults['memory'], val.Number(int, 'POS'))
self._arg('gpumemory', 'int', 'Only run on GPUs with at least this much memory. Needs special setup of SLURM. '
'Check how to define gpu_mem on SLURM.', None, val.Number(int, '0POS'))
self._arg('walltime', 'int', 'Job timeout (s)', self._defaults['walltime'], val.Number(int, 'POS'))
self._arg('environment', 'str', 'Envvars to propagate to the job.', self._defaults['environment'], val.String())
self._arg('mailtype', 'str', 'When to send emails. Separate options with commas like \'END,FAIL\'.', None, val.String())
self._arg('mailuser', 'str', 'User email address.', None, val.String())
self._arg('outputstream', 'str', 'Output stream.', 'slurm.%N.%j.out', val.String())
self._arg('errorstream', 'str', 'Error stream.', 'slurm.%N.%j.err'), val.String() # Maybe change these to job name
self._arg('datadir', 'str', 'The path in which to store completed trajectories.', None, val.String())
self._arg('trajext', 'str', 'Extension of trajectory files. This is needed to copy them to datadir.', 'xtc',
val.String())
self._arg('nodelist', 'list', 'A list of nodes on which to run every job at the *same time*! Careful! The jobs'
' will be duplicated!', None, val.String(), nargs='*')
self._arg('exclude', 'list', 'A list of nodes on which *not* to run the jobs. Use this to select nodes on '
'which to allow the jobs to run on.', None, val.String(), nargs='*')
# Load Slurm configuration profile
slurmconfig = _config['slurm']
profile = None
if _configapp is not None:
if slurmconfig is not None:
if os.path.isfile(slurmconfig) and slurmconfig.endswith(('.yml', '.yaml')):
try:
with open(slurmconfig, 'r') as f:
profile = yaml.load(f)
logger.info('Loaded Slurm configuration YAML file {}'.format(slurmconfig))
except:
logger.warning('Could not load YAML file {}'.format(slurmconfig))
else:
logger.warning('{} does not exist or it is not a YAML file.'.format(slurmconfig))
if profile:
try:
properties = profile[_configapp]
except:
raise RuntimeError('There is no profile in {} for configuration '
'app {}'.format(slurmconfig, _configapp))
for p in properties:
self.__dict__[p] = properties[p]
logger.info('Setting {} to {}'.format(p, properties[p]))
else:
raise RuntimeError('No Slurm configuration YAML file defined for the configapp')
else:
if slurmconfig is not None:
logger.warning('Slurm configuration YAML file defined without configuration app')
# Find executables
self._qsubmit = SlurmQueue._find_binary('sbatch')
self._qinfo = SlurmQueue._find_binary('sinfo')
self._qcancel = SlurmQueue._find_binary('scancel')
self._qstatus = SlurmQueue._find_binary('squeue')
def __init__(self,
_configapp=None,
_configfile=None,
_findExecutables=True,
_logger=True):
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg(
"version",
"int",
"LSF major version",
self._defaults["version"],
valid_values=[9, 10],
)
self._arg("jobname", "str", "Job name (identifier)", None,
val.String())
self._arg(
"queue",
"list",
"The queue or list of queues to run on. If list, it attempts to submit the job to "
"the first queue listed",
self._defaults["queue"],
val.String(),
nargs="*",
)
self._arg("app", "str", "The application profile",
self._defaults["app"], val.String())
self._arg(
"ngpu",
"int",
"Number of GPUs to use for a single job",
self._defaults["ngpu"],
val.Number(int, "0POS"),
)
self._arg(
"gpu_options",
"dict",
"Number of GPUs to use for a single job",
self._defaults["gpu_options"],
val.Dictionary(
key_type=str,
valid_keys=["mode", "mps", "j_exclusive"],
value_type={
"mode": str,
"mps": str,
"j_exclusive": str
},
valid_values={
"mode": ["shared", "exclusive_process"],
"mps": ["yes", "no"],
"j_exclusive": ["yes", "no"],
},
),
)
self._arg(
"ncpu",
"int",
"Number of CPUs to use for a single job",
self._defaults["ncpu"],
val.Number(int, "0POS"),
)
self._arg(
"memory",
"int",
"Amount of memory per job (KB)",
self._defaults["memory"],
val.Number(int, "0POS"),
)
self._arg(
"walltime",
"int",
"Job timeout (hour:min or min)",
self._defaults["walltime"],
val.Number(int, "0POS"),
)
self._arg(
"resources",
"list",
"Resources of the queue",
self._defaults["resources"],
val.String(),
nargs="*",
)
self._cmdDeprecated("environment", "prerun")
self._arg("outputstream", "str", "Output stream.", "lsf.%J.out",
val.String())
self._arg("errorstream", "str", "Error stream.", "lsf.%J.err",
val.String())
self._arg(
"datadir",
"str",
"The path in which to store completed trajectories.",
None,
val.String(),
)
self._arg(
"trajext",
"str",
"Extension of trajectory files. This is needed to copy them to datadir.",
"xtc",
val.String(),
)
self._arg(
"envvars",
"str",
"Envvars to propagate from submission node to the running node (comma-separated)",
self._defaults["envvars"],
val.String(),
)
self._arg(
"prerun",
"list",
"Shell commands to execute on the running node before the job (e.g. "
"loading modules)",
self._defaults["prerun"],
val.String(),
nargs="*",
)
# Load LSF configuration profile
loadConfig(self, "lsf", _configfile, _configapp, _logger)
# Find executables
if _findExecutables:
self._qsubmit = LsfQueue._find_binary("bsub")
self._qinfo = LsfQueue._find_binary("bqueues")
self._qcancel = LsfQueue._find_binary("bkill")
self._qstatus = LsfQueue._find_binary("bjobs")
def __init__(self,
_configapp=None,
_configfile=None,
_findExecutables=True,
_logger=True):
SimQueue.__init__(self)
ProtocolInterface.__init__(self)
self._arg("jobname", "str", "Job name (identifier)", None,
val.String())
self._arg(
"queue",
"list",
"The queue or list of queues to run on. If list, it attempts to submit the job to "
"the first queue listed",
self._defaults["queue"],
val.String(),
nargs="*",
)
self._arg(
"ngpu",
"int",
"Number of GPUs to use for a single job",
self._defaults["ngpu"],
val.Number(int, "0POS"),
)
self._arg(
"ncpu",
"int",
"Number of CPUs to use for a single job",
self._defaults["ncpu"],
val.Number(int, "0POS"),
)
self._arg(
"memory",
"int",
"Amount of memory per job (MiB)",
self._defaults["memory"],
val.Number(int, "0POS"),
)
self._arg(
"walltime",
"int",
"Job timeout (hour:min or min)",
self._defaults["walltime"],
val.Number(int, "0POS"),
)
self._arg(
"pe",
"str",
"SGE Parallel Environment",
self._defaults["pe"],
val.String(),
)
self._arg(
"resources",
"list",
"Resources of the queue",
self._defaults["resources"],
val.String(),
nargs="*",
)
self._cmdDeprecated("environment", "prerun")
self._arg(
"outputstream",
"str",
"Output stream.",
"$REQUEST.oJID[.TASKID]",
val.String(),
)
self._arg(
"errorstream",
"str",
"Error stream.",
"$REQUEST.eJID[.TASKID]",
val.String(),
)
self._arg(
"datadir",
"str",
"The path in which to store completed trajectories.",
None,
val.String(),
)
self._arg(
"trajext",
"str",
"Extension of trajectory files. This is needed to copy them to datadir.",
"xtc",
val.String(),
)
self._arg(
"envvars",
"str",
"Envvars to propagate from submission node to the running node (comma-separated)",
self._defaults["envvars"],
val.String(),
)
self._arg(
"prerun",
"list",
"Shell commands to execute on the running node before the job (e.g. "
"loading modules)",
self._defaults["prerun"],
val.String(),
nargs="*",
)
# Load SGE configuration profile
loadConfig(self, "sge", _configfile, _configapp, _logger)
# Find executables
if _findExecutables:
self._qsubmit = SgeQueue._find_binary("qsub")
self._qinfo = SgeQueue._find_binary("qhost")
self._qcancel = SgeQueue._find_binary("qdel")
self._qstatus = SgeQueue._find_binary("qstat")
self._checkQueue()