def __init__(self,
channel=LocalChannel(),
account=None,
queue=None,
scheduler_options='',
worker_init='',
nodes_per_block=1,
init_blocks=1,
min_blocks=0,
max_blocks=100,
parallelism=1,
launcher=AprunLauncher(),
walltime="00:20:00",
cmd_timeout=120):
label = 'torque'
super().__init__(label,
channel,
nodes_per_block,
init_blocks,
min_blocks,
max_blocks,
parallelism,
walltime,
launcher,
cmd_timeout=cmd_timeout)
self.account = account
self.queue = queue
self.scheduler_options = scheduler_options
self.worker_init = worker_init
self.provisioned_blocks = 0
self.template_string = template_string
# Dictionary that keeps track of jobs, keyed on job_id
self.resources = {}
def __init__(self,
channel=LocalChannel(),
nodes_per_block=1,
init_blocks=0,
min_blocks=0,
max_blocks=1,
parallelism=1,
walltime="00:10:00",
account=None,
queue=None,
scheduler_options='',
worker_init='',
launcher=AprunLauncher(),
cmd_timeout=10):
label = 'cobalt'
super().__init__(label,
channel=channel,
nodes_per_block=nodes_per_block,
init_blocks=init_blocks,
min_blocks=min_blocks,
max_blocks=max_blocks,
parallelism=parallelism,
walltime=walltime,
launcher=launcher,
cmd_timeout=cmd_timeout)
self.account = account
self.queue = queue
self.scheduler_options = scheduler_options
self.worker_init = worker_init
def local_setup():
threads_config = Config(
executors=[
HighThroughputExecutor(
label="theta_htex",
# worker_debug=True,
cores_per_worker=4,
provider=CobaltProvider(
queue='debug-flat-quad',
account='CSC249ADCD01',
launcher=AprunLauncher(overrides="-d 64"),
worker_init='source activate parsl-issues',
init_blocks=1,
max_blocks=1,
min_blocks=1,
nodes_per_block=4,
cmd_timeout=60,
walltime='00:10:00',
),
)
],
monitoring=MonitoringHub(hub_port=55055,
logging_level=logging.DEBUG,
resource_monitoring_interval=10),
strategy=None)
parsl.load(threads_config)
def fresh_config():
config = Config(
executors=[
HighThroughputExecutor(
label="bw_htex",
cores_per_worker=1,
worker_debug=False,
max_workers=1,
address=address_by_hostname(),
provider=TorqueProvider(
queue='normal',
launcher=AprunLauncher(overrides="-b -- bwpy-environ --"),
# string to prepend to #SBATCH blocks in the submit
# script to the scheduler eg: '#SBATCH --constraint=knl,quad,cache'
scheduler_options='',
# Command to be run before starting a worker, such as:
# 'module load Anaconda; source activate parsl_env'.
worker_init=user_opts['bluewaters']['worker_init'],
init_blocks=1,
max_blocks=1,
min_blocks=1,
nodes_per_block=2,
walltime='00:30:00',
cmd_timeout=120,
),
)
], )
return config
def fresh_config():
return Config(
executors=[
HighThroughputExecutor(
label='theta_local_htex_multinode',
max_workers=1,
address=address_by_hostname(),
provider=CobaltProvider(
queue=user_opts['theta']['queue'],
account=user_opts['theta']['account'],
launcher=AprunLauncher(overrides="-d 64"),
walltime='00:10:00',
nodes_per_block=2,
init_blocks=1,
max_blocks=1,
# string to prepend to #COBALT blocks in the submit
# script to the scheduler eg: '#COBALT -t 50'
scheduler_options='',
# Command to be run before starting a worker, such as:
# 'module load Anaconda; source activate parsl_env'.
worker_init=user_opts['theta']['worker_init'],
cmd_timeout=120,
),
)
], )
def theta_nwchem_config(log_dir: str,
nodes_per_nwchem: int = 2,
total_nodes: int = int(
os.environ.get("COBALT_JOBSIZE", 1)),
ml_prefetch: int = 0) -> Config:
"""Theta configuration where QC workers sit on the launch node (to be able to aprun)
and ML workers are placed on compute nodes
Args:
nodes_per_nwchem: Number of nodes per NWChem computation
log_dir: Path to store monitoring DB and parsl logs
total_nodes: Total number of nodes available. Default: COBALT_JOBSIZE
ml_prefetch: Number of tasks for ML workers to prefetch for inference
Returns:
(Config) Parsl configuration
"""
assert total_nodes % nodes_per_nwchem == 0, "NWChem node count not a multiple of nodes per task"
nwc_workers = total_nodes // nodes_per_nwchem
return Config(
executors=[
ThreadPoolExecutor(label='qc', max_threads=nwc_workers),
HighThroughputExecutor(
address=address_by_hostname(),
label="ml",
max_workers=1,
prefetch_capacity=ml_prefetch,
provider=LocalProvider(
nodes_per_block=
nodes_per_nwchem, # Minimum increment in blcoks
init_blocks=0,
max_blocks=total_nodes //
nodes_per_nwchem, # Limits the number of manager processes,
launcher=AprunLauncher(
overrides='-d 256 --cc depth -j 4'
), # Places worker on the compute node
worker_init='''
module load miniconda-3
conda activate /lus/theta-fs0/projects/CSC249ADCD08/edw/env
''',
),
)
],
monitoring=MonitoringHub(
hub_address=address_by_hostname(),
monitoring_debug=False,
resource_monitoring_interval=10,
logdir=log_dir,
logging_endpoint=
f'sqlite:///{os.path.join(log_dir, "monitoring.db")}'),
run_dir=log_dir,
strategy='simple',
max_idletime=15.)
def parsl_config(name: str) -> Tuple[Config, int]:
"""Make the compute resource configuration
Args:
name: Name of the diesred configuration
Returns:
- Parsl compute configuration
- Number of compute slots: Includes execution slots and pre-fetch buffers
"""
if name == 'local':
return Config(
executors=[
HighThroughputExecutor(max_workers=16, prefetch_capacity=1)
]
), 64
elif name == 'theta-debug':
return Config(
retries=16,
executors=[HighThroughputExecutor(
address=address_by_hostname(),
label="debug",
max_workers=64,
prefetch_capacity=64,
cpu_affinity='block',
provider=CobaltProvider(
account='redox_adsp',
queue='debug-flat-quad',
nodes_per_block=8,
scheduler_options='#COBALT --attrs enable_ssh=1',
walltime='00:60:00',
init_blocks=0,
max_blocks=1,
cmd_timeout=360,
launcher=AprunLauncher(overrides='-d 64 --cc depth -j 1'),
worker_init='''
module load miniconda-3
conda activate /lus/theta-fs0/projects/CSC249ADCD08/edw/env''',
),
)]
), 64 * 8 * 4
else:
raise ValueError(f'Configuration not defined: {name}')
with Pool(args.local_workers) as p:
database['invalid'] = p.map(is_smiles_valid, database['smiles'])
database.query('not invalid', inplace=True)
logging.info(f'Found {len(database)} valid SMILES')
# Define the Parsl configuration
config = Config(
executors=[
HighThroughputExecutor(
address=address_by_hostname(),
label="htex",
max_workers=1,
provider=CobaltProvider(
queue='CVD_Research',
account='CVD_Research',
launcher=AprunLauncher(overrides="-d 64 --cc depth"),
walltime='3:00:00',
nodes_per_block=64,
init_blocks=1,
min_blocks=1,
max_blocks=4,
scheduler_options='#COBALT --attrs enable_ssh=1',
worker_init='''
module load miniconda-3
source activate /home/lward/exalearn/covid/toxicity-prediction/deepchem/env
export KMP_AFFINITY=disabled
which python
''',
cmd_timeout=120,
),
),
def theta_xtb_config(log_dir: str,
xtb_per_node: int = 1,
ml_tasks_per_node: int = 1,
total_nodes: int = int(os.environ.get(
"COBALT_JOBSIZE", 1))):
"""Theta configuration where QC tasks and ML tasks run on single nodes.
There are no MPI tasks in this configuration.
Args:
ml_workers: Number of nodes dedicated to ML tasks
xtb_per_node: Number of XTB calculations
ml_tasks_per_node: Number of ML tasks to place on each node
log_dir: Path to store monitoring DB and parsl logs
total_nodes: Total number of nodes available. Default: COBALT_JOBSIZE
Returns:
(Config) Parsl configuration
"""
return Config(
executors=[
HighThroughputExecutor(
address=address_by_hostname(),
label="qc",
max_workers=xtb_per_node,
cpu_affinity='block',
provider=LocalProvider(
nodes_per_block=total_nodes,
init_blocks=0,
max_blocks=1,
launcher=AprunLauncher(
overrides='-d 64 --cc depth'
), # Places worker on the compute node
worker_init='''
module load miniconda-3
conda activate /lus/theta-fs0/projects/CSC249ADCD08/edw/env
''',
),
),
HighThroughputExecutor(
address=address_by_hostname(),
label="ml",
max_workers=ml_tasks_per_node,
cpu_affinity='block',
provider=LocalProvider(
nodes_per_block=total_nodes,
init_blocks=1,
max_blocks=1,
launcher=AprunLauncher(
overrides='-d 64 --cc depth'
), # Places worker on the compute node
worker_init='''
module load miniconda-3
conda activate /lus/theta-fs0/projects/CSC249ADCD08/edw/env
''',
),
)
],
monitoring=MonitoringHub(
hub_address=address_by_hostname(),
hub_port=55055,
monitoring_debug=False,
resource_monitoring_interval=10,
logdir=log_dir,
logging_endpoint=
f'sqlite:///{os.path.join(log_dir, "monitoring.db")}'),
run_dir=log_dir,
strategy='simple',
max_idletime=15.)
def theta_nwchem_config(ml_workers: int, log_dir: str, nodes_per_nwchem: int = 2,
total_nodes: int = int(os.environ.get("COBALT_JOBSIZE", 1))) -> Config:
"""Theta configuration where QC workers sit on the launch node (to be able to aprun)
and ML workers are placed on compute nodes
Args:
ml_workers: Number of nodes dedicated to ML tasks
nodes_per_nwchem: Number of nodes per NWChem computation
log_dir: Path to store monitoring DB and parsl logs
total_nodes: Total number of nodes available. Default: COBALT_JOBSIZE
Returns:
(Config) Parsl configuration
"""
nwc_nodes = total_nodes - ml_workers
assert nwc_nodes % nodes_per_nwchem == 0, "NWChem node count not a multiple of nodes per task"
nwc_workers = nwc_nodes // nodes_per_nwchem
return Config(
executors=[
HighThroughputExecutor(
address=address_by_hostname(),
label="qc",
max_workers=nwc_workers,
cores_per_worker=1e-6,
provider=LocalProvider(
nodes_per_block=1,
init_blocks=1,
max_blocks=1,
launcher=SimpleLauncher(), # Places worker on the launch node
worker_init='''
module load miniconda-3
conda activate /lus/theta-fs0/projects/CSC249ADCD08/edw/env
''',
),
),
HighThroughputExecutor(
address=address_by_hostname(),
label="ml",
max_workers=1,
provider=LocalProvider(
nodes_per_block=ml_workers,
init_blocks=1,
max_blocks=1,
launcher=AprunLauncher(overrides='-d 64 --cc depth'), # Places worker on the compute node
worker_init='''
module load miniconda-3
conda activate /lus/theta-fs0/projects/CSC249ADCD08/edw/env
''',
),
)
],
monitoring=MonitoringHub(
hub_address=address_by_hostname(),
monitoring_debug=False,
resource_monitoring_interval=10,
logdir=log_dir,
logging_endpoint=f'sqlite:///{os.path.join(log_dir, "monitoring.db")}'
),
run_dir=log_dir,
strategy=None,
)
def theta_persistent(log_dir: str,
nodes_per_nwchem: int = 1,
qc_nodes: int = 8,
ml_nodes: int = 8,
ml_prefetch: int = 0) -> Config:
"""Configuration where the application is persistent and sits on the Theta login node.
Nodes will be requested from Cobalt using separate jobs for ML and QC tasks.
Args:
nodes_per_nwchem: Number of nodes per NWChem computation
log_dir: Path to store monitoring DB and parsl logs
qc_nodes: Number of nodes dedicated to QC tasks
ml_prefetch: Number of tasks for ML workers to prefetch for inference
Returns:
(Config) Parsl configuration
"""
return Config(
retries=8,
executors=[
HighThroughputExecutor(
address=address_by_hostname(),
label="qc",
max_workers=qc_nodes // nodes_per_nwchem,
prefetch_capacity=ml_prefetch,
provider=CobaltProvider(
account='CSC249ADCD08',
queue='debug-cache-quad' if qc_nodes <= 8 else None,
walltime='00:60:00',
nodes_per_block=qc_nodes,
init_blocks=0,
max_blocks=1,
launcher=SimpleLauncher(),
cmd_timeout=360,
worker_init='''
module load miniconda-3
conda activate /lus/theta-fs0/projects/CSC249ADCD08/edw/env
export OMP_NUM_THREADS=64
export KMP_INIT_AT_FORK=FALSE
export PYTHONPATH=$PYTHONPATH:$(pwd)
export PATH="/lus/theta-fs0/projects/CSC249ADCD08/software/nwchem-6.8.1/bin/LINUX64:$PATH"
mkdir -p scratch # For the NWChem tasks
pwd
which nwchem
hostname
module load atp
export MPICH_GNI_MAX_EAGER_MSG_SIZE=16384
export MPICH_GNI_MAX_VSHORT_MSG_SIZE=10000
export MPICH_GNI_MAX_EAGER_MSG_SIZE=131072
export MPICH_GNI_NUM_BUFS=300
export MPICH_GNI_NDREG_MAXSIZE=16777216
export MPICH_GNI_MBOX_PLACEMENT=nic
export MPICH_GNI_LMT_PATH=disabled
export COMEX_MAX_NB_OUTSTANDING=6
export LD_LIBRARY_PATH=/opt/intel/mkl/lib/intel64_lin/:/opt/intel/compilers_and_libraries_2020.0.166/linux/compiler/lib/intel64_lin:$LD_LIBRARY_PATH
''',
),
),
HighThroughputExecutor(
address=address_by_hostname(),
label="ml",
max_workers=1,
prefetch_capacity=ml_prefetch,
provider=CobaltProvider(
account='CSC249ADCD08',
queue='debug-flat-quad',
nodes_per_block=ml_nodes,
scheduler_options='#COBALT --attrs enable_ssh=1',
walltime='00:60:00',
init_blocks=0,
max_blocks=1,
cmd_timeout=360,
launcher=AprunLauncher(
overrides='-d 256 --cc depth -j 4'
), # Places worker on the compute node
worker_init='''
module load miniconda-3
conda activate /lus/theta-fs0/projects/CSC249ADCD08/edw/env''',
),
)
],
run_dir=log_dir,
strategy='simple',
max_idletime=15.)
],
strategy=None
)
# Configuration to run on Theta using single-app applications
theta_config = Config(
executors=[
HighThroughputExecutor(
address=address_by_hostname(),
label="htex",
max_workers=8,
provider=LocalProvider(
nodes_per_block=os.environ.get("COBALT_JOBSIZE", 1),
init_blocks=1,
max_blocks=1,
launcher=AprunLauncher(overrides='-d 64 --cc depth'),
worker_init='''
module load miniconda-3
export PATH=~/software/psi4/bin:$PATH
conda activate /lus/theta-fs0/projects/CSC249ADCD08/colmena/env
export KMP_INIT_AT_FORK=FALSE
export OMP_NUM_THREADS=8
''',
),
),
ThreadPoolExecutor(label="local_threads", max_threads=4)
],
strategy=None,
)
theta_nwchem_config = Config(
aprun_overrides = """-cc depth -j 1 -d 64"""
theta_executor = HighThroughputExecutor(
label='worker-nodes',
address=address_by_hostname(),
worker_debug=True,
suppress_failure=False,
poll_period=5000,
cores_per_worker=256,
heartbeat_period=300,
heartbeat_threshold=1200,
provider=LocalProvider(nodes_per_block=8,
init_blocks=1,
min_blocks=1,
max_blocks=1,
launcher=AprunLauncher(overrides=aprun_overrides),
walltime=WALLTIME),
)
cori_in_salloc_executor = HighThroughputExecutor(
label='worker-nodes',
address=address_by_hostname(),
worker_debug=True,
suppress_failure=True,
poll_period=5000,
cores_per_worker=272,
heartbeat_period=300,
heartbeat_threshold=1200,
provider=LocalProvider(nodes_per_block=299,
init_blocks=1,
min_blocks=1,
strategy=None,
)
config = Config(
retries=1,
usage_tracking=True,
executors=[
HighThroughputExecutor(
address=address_by_hostname(),
label="htex",
max_workers=4,
prefetch_capacity=1,
provider=CobaltProvider(
queue='CVD_Research',
account='CVD_Research',
launcher=AprunLauncher(overrides="-d 256 --cc depth -j 4"),
walltime='3:00:00',
nodes_per_block=4,
init_blocks=1,
min_blocks=1,
max_blocks=4,
scheduler_options='#COBALT --attrs enable_ssh=1',
worker_init=f'''
module load miniconda-3
module load java
source activate /home/lward/exalearn/covid/toxicity-prediction/opera/env
export KMP_AFFINITY=disabled
which python
# Set the environment variables
{envs}
HighThroughputExecutor(
label='theta_local_htex_multinode',
max_workers=
32, # The target process itself if a Multiprocessing application. We do not
# need to overload the compute node with parsl workers.
address="10.236.1.195",
# address=address_by_hostname(),
# launch_cmd=launch_cmd,
prefetch_capacity=2,
provider=CobaltProvider(
#queue='debug-flat-quad',
#queue='default',
queue='CVD_Research',
#account='candle_aesp',
account='CVD_Research',
launcher=AprunLauncher(overrides=" -d 64"),
walltime='02:00:00',
nodes_per_block=25,
init_blocks=1,
min_blocks=1,
max_blocks=1,
# string to prepend to #COBALT blocks in the submit
# script to the scheduler eg: '#COBALT -t 50'
# scheduler_options='',
# Command to be run before starting a worker, such as:
# 'module load Anaconda; source activate parsl_env'.
# worker_init='source ~/Anaconda/bin/activate; conda activate candle_py3.7;',
worker_init=
'source ~/anaconda3/bin/activate; conda activate candle_py3.7;',
#worker_init=("bash /projects/candle_aesp/yadu/unpack_and_load.sh tmp candle_py3.7 /projects/candle_aesp/yadu/candle_py3.7.tar.gz /dev/shm/ ;"
# "source /dev/shm/candle_py3.7/bin/activate ;"
from parsl.config import Config
from parsl.executors import HighThroughputExecutor
# If you are a developer running tests, make sure to update parsl/tests/configs/user_opts.py
# If you are a user copying-and-pasting this as an example, make sure to either
# 1) create a local `user_opts.py`, or
# 2) delete the user_opts import below and replace all appearances of `user_opts` with the literal value
# (i.e., user_opts['swan']['username'] -> 'your_username')
from .user_opts import user_opts
config = Config(
executors=[
HighThroughputExecutor(
label='swan_htex',
provider=TorqueProvider(
channel=SSHChannel(
hostname='swan.cray.com',
username=user_opts['swan']['username'],
script_dir=user_opts['swan']['script_dir'],
),
nodes_per_block=1,
init_blocks=1,
max_blocks=1,
launcher=AprunLauncher(),
scheduler_options=user_opts['swan']['scheduler_options'],
worker_init=user_opts['swan']['worker_init'],
),
)
]
)
from parsl.launchers import AprunLauncher
from parsl.providers import TorqueProvider
from parsl.config import Config
from parsl.executors import HighThroughputExecutor
from parsl.addresses import address_by_hostname
from parsl.data_provider.scheme import GlobusScheme
config = Config(executors=[
HighThroughputExecutor(
label="bluewaters_htex",
worker_debug=True,
address="<LOGIN_NODE>",
provider=TorqueProvider(
channel=LocalChannel(),
init_blocks=1,
max_blocks=1,
min_blocks=1,
nodes_per_block=1,
launcher=AprunLauncher(overrides="-b -- bwpy-environ --"),
scheduler_options='''#PBS -l nodes=1:ppn=32
#PBS -q debug''',
worker_init='''module load bwpy''',
walltime='00:30:00'),
storage_access=[
GlobusScheme(endpoint_uuid="d59900ef-6d04-11e5-ba46-22000b92c6ec",
endpoint_path="/",
local_path="/")
])
], )
