from funcx_endpoint.endpoint.utils.config import Config
from funcx_endpoint.executors import HighThroughputExecutor
from parsl.providers import LocalProvider
...
config = Config(executors=[
HighThroughputExecutor(
label="fe.cs.uchicago",
address=address_by_hostname(),
provider=SlurmProvider(
channel=LocalChannel(),
nodes_per_block=NODES_PER_JOB,
init_blocks=1,
partition="general",
launcher=SrunLauncher(
overrides=(f"hostname; srun --ntasks={TOTAL_WORKERS} "
f"--ntasks-per-node={WORKERS_PER_NODE} "
f"--gpus-per-task=rtx2080ti:{GPUS_PER_WORKER} "
f"--gpu-bind=map_gpu:{GPU_MAP}")),
walltime="01:00:00",
),
)
], )
def cli_run():
parser = argparse.ArgumentParser()
parser.add_argument("-c",
"--client_address",
required=True,
help="Client address")
parser.add_argument(
"--client_ports",
required=True,
help="client ports as a triple of outgoing,incoming,command",
)
parser.add_argument("--worker_port_range",
help="Worker port range as a tuple")
parser.add_argument(
"-l",
"--logdir",
default="./parsl_worker_logs",
help="Parsl worker log directory",
)
parser.add_argument(
"--worker_ports",
default=None,
help="OPTIONAL, pair of workers ports to listen on, "
"e.g. --worker_ports=50001,50005",
)
parser.add_argument(
"--suppress_failure",
action="store_true",
help="Enables suppression of failures",
)
parser.add_argument(
"--endpoint_id",
required=True,
help="Endpoint ID, used to identify the endpoint to the remote broker",
)
parser.add_argument("--hb_threshold",
help="Heartbeat threshold in seconds")
parser.add_argument(
"--config",
default=None,
help="Configuration object that describes provisioning",
)
parser.add_argument("-d",
"--debug",
action="store_true",
help="Enables debug logging")
print("Starting HTEX Intechange")
args = parser.parse_args()
logdir = os.path.abspath(args.logdir)
os.makedirs(logdir, exist_ok=True)
setup_logging(logfile=os.path.join(logdir, "endpoint.log"),
debug=args.debug)
optionals = {}
optionals["suppress_failure"] = args.suppress_failure
optionals["logdir"] = os.path.abspath(args.logdir)
optionals["client_address"] = args.client_address
optionals["client_ports"] = [int(i) for i in args.client_ports.split(",")]
optionals["endpoint_id"] = args.endpoint_id
# DEBUG ONLY : TODO: FIX
if args.config is None:
from parsl.providers import LocalProvider
from funcx_endpoint.endpoint.utils.config import Config
config = Config(
worker_debug=True,
scaling_enabled=True,
provider=LocalProvider(
init_blocks=1,
min_blocks=1,
max_blocks=1,
),
max_workers_per_node=2,
funcx_service_address="http://127.0.0.1:8080",
)
optionals["config"] = config
else:
optionals["config"] = args.config
if args.worker_ports:
optionals["worker_ports"] = [
int(i) for i in args.worker_ports.split(",")
]
if args.worker_port_range:
optionals["worker_port_range"] = [
int(i) for i in args.worker_port_range.split(",")
]
ic = EndpointInterchange(**optionals)
ic.start()
"""
from funcx_endpoint.endpoint.utils.config import Config
config = Config()
if __name__ == '__main__':
import funcx
import os
import logging
funcx.set_stream_logger()
logger = logging.getLogger(__file__)
endpoint_dir = "/home/yadu/.funcx/default"
if config.working_dir is None:
working_dir = "{}/{}".format(endpoint_dir, "worker_logs")
# if self.worker_logdir_root is not None:
# worker_logdir = "{}/{}".format(self.worker_logdir_root, self.label)
print("Loading : ", config)
# Set script dir
config.provider.script_dir = working_dir
config.provider.channel.script_dir = os.path.join(working_dir,
'submit_scripts')
config.provider.channel.makedirs(config.provider.channel.script_dir,
exist_ok=True)
os.makedirs(config.provider.script_dir, exist_ok=True)
debug_opts = "--debug" if config.worker_debug else ""
max_workers = "" if config.max_workers_per_node == float('inf') \
else "--max_workers={}".format(config.max_workers_per_node)
config = Config(
executors=[
HighThroughputExecutor(
label="fe.cs.uchicago",
worker_debug=False,
address=address_by_hostname(),
provider=SlurmProvider(
partition='general',
# Launch 4 managers per node, each bound to 1 GPU
# This is a hack. We use hostname ; to terminate the srun command, and
# start our own
#
# DO NOT MODIFY unless you know what you are doing.
launcher=SrunLauncher(
overrides=(f'hostname; srun --ntasks={TOTAL_WORKERS} '
f'--ntasks-per-node={WORKERS_PER_NODE} '
f'--gpus-per-task=rtx2080ti:{GPUS_PER_WORKER} '
f'--gpu-bind=map_gpu:{GPU_MAP}')),
# Scale between 0-1 blocks with 2 nodes per block
nodes_per_block=NODES_PER_JOB,
init_blocks=0,
min_blocks=0,
max_blocks=1,
# Hold blocks for 30 minutes
walltime='00:30:00',
),
)
], )
from funcx_endpoint.endpoint.utils.config import Config
from parsl.providers import LocalProvider
config = Config(scaling_enabled=True,
provider=LocalProvider(
init_blocks=1,
min_blocks=1,
max_blocks=1,
),
max_workers_per_node=2,
funcx_service_address='https://api.funcx.org/v1')
# For now, visible_to must be a list of URNs for globus auth users or groups, e.g.:
# urn:globus:auth:identity:{user_uuid}
# urn:globus:groups:id:{group_uuid}
meta = {
"name": "$name",
"description": "",
"organization": "",
"department": "",
"public": False,
"visible_to": []
}
config = Config(
executors=[
HighThroughputExecutor(
max_workers_per_node=2,
worker_debug=False,
address=address_by_hostname(),
provider=SlurmProvider(
partition=user_opts['frontera']['partition'],
launcher=SrunLauncher(),
# Enter scheduler_options if needed
scheduler_options=user_opts['frontera']['scheduler_options'],
# Command to be run before starting a worker, such as:
# 'module load Anaconda; source activate parsl_env'.
worker_init=user_opts['frontera']['worker_init'],
# Add extra time for slow scheduler responses
cmd_timeout=60,
# Scale between 0-1 blocks with 2 nodes per block
nodes_per_block=2,
init_blocks=0,
min_blocks=0,
max_blocks=1,
# Hold blocks for 30 minutes
walltime='00:30:00',
),
)
], )
}
config = Config(
executors=[
HighThroughputExecutor(
max_workers_per_node=1,
worker_debug=False,
address=address_by_hostname(),
provider=TorqueProvider(
queue='normal',
launcher=AprunLauncher(overrides="-b -- bwpy-environ --"),
# string to prepend to #SBATCH blocks in the submit
scheduler_options=user_opts['bluewaters']['scheduler_options'],
# Command to be run before starting a worker, such as:
# 'module load bwpy; source activate funcx env'.
worker_init=user_opts['bluewaters']['worker_init'],
# Scale between 0-1 blocks with 2 nodes per block
nodes_per_block=2,
init_blocks=0,
min_blocks=0,
max_blocks=1,
# Hold blocks for 30 minutes
walltime='00:30:00'),
)
], )
# fmt: on
config = Config(
executors=[
HighThroughputExecutor(
max_workers_per_node=1,
worker_debug=False,
address=address_by_hostname(),
scheduler_mode='soft',
worker_mode='singularity_reuse',
container_type='singularity',
container_cmd_options="-H /home/$USER",
provider=CobaltProvider(
queue='debug-flat-quad',
account=user_opts['theta']['account'],
launcher=AprunLauncher(overrides="-d 64"),
# string to prepend to #COBALT blocks in the submit
# script to the scheduler eg: '#COBALT -t 50'
scheduler_options=user_opts['theta']['scheduler_options'],
# Command to be run before starting a worker, such as:
# 'module load Anaconda; source activate funcx_env'.
worker_init=user_opts['theta']['worker_init'],
# Scale between 0-1 blocks with 2 nodes per block
nodes_per_block=2,
init_blocks=0,
min_blocks=0,
max_blocks=1,
# Hold blocks for 30 minutes
walltime='00:30:00'
),
)
],
)
import argparse
from funcx_endpoint.endpoint.utils.config import Config
from funcx_endpoint.executors.high_throughput.interchange import Interchange
import funcx
funcx.set_stream_logger()
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("-a", "--address", required=True, help="Address")
parser.add_argument("-c", "--client_ports", required=True, help="ports")
args = parser.parse_args()
config = Config()
ic = Interchange(
config,
client_address=args.address,
client_ports=[int(i) for i in args.client_ports.split(',')],
)
ic.start()
print("Interchange started")
}
config = Config(
executors=[
HighThroughputExecutor(
max_workers_per_node=2,
worker_debug=False,
address=address_by_hostname(),
provider=SlurmProvider(
partition='broadwl',
launcher=SrunLauncher(),
# string to prepend to #SBATCH blocks in the submit
# script to the scheduler eg: '#SBATCH --constraint=knl,quad,cache'
scheduler_options=user_opts['midway']['scheduler_options'],
# Command to be run before starting a worker, such as:
# 'module load Anaconda; source activate parsl_env'.
worker_init=user_opts['midway']['worker_init'],
# Scale between 0-1 blocks with 2 nodes per block
nodes_per_block=2,
init_blocks=0,
min_blocks=0,
max_blocks=1,
# Hold blocks for 30 minutes
walltime='00:30:00'),
)
], )
# fmt: on
}
config = Config(
executors=[
HighThroughputExecutor(
label='Kubernetes_funcX',
max_workers_per_node=1,
address=address_by_route(),
scheduler_mode='hard',
container_type='docker',
strategy=KubeSimpleStrategy(max_idletime=3600),
provider=KubernetesProvider(
init_blocks=0,
min_blocks=0,
max_blocks=2,
init_cpu=1,
max_cpu=4,
init_mem="1024Mi",
max_mem="4096Mi",
image=user_opts['kube']['image'],
worker_init=user_opts['kube']['worker_init'],
namespace=user_opts['kube']['namespace'],
incluster_config=False,
),
)
],
heartbeat_period=15,
heartbeat_threshold=200,
log_dir='.',
)
# fmt: on
from parsl.providers import LocalProvider
from funcx_endpoint.endpoint.utils.config import Config
from funcx_endpoint.executors import HighThroughputExecutor
config = Config(
executors=[
HighThroughputExecutor(provider=LocalProvider(
init_blocks=1,
min_blocks=0,
max_blocks=1,
), )
],
funcx_service_address="https://api2.funcx.org/v2",
)
# For now, visible_to must be a list of URNs for globus auth users or groups, e.g.:
# urn:globus:auth:identity:{user_uuid}
# urn:globus:groups:id:{group_uuid}
meta = {
"name": "$name",
"description": "",
"organization": "",
"department": "",
"public": False,
"visible_to": [],
}
# Set ncpus=32, otherwise it defaults to 1 on Polaris
'scheduler_options': '',
}
}
config = Config(
executors=[
HighThroughputExecutor(
max_workers_per_node=1,
strategy=SimpleStrategy(max_idletime=300),
# IP of Polaris testbed login node
address='10.230.2.72',
provider=PBSProProvider(
launcher=SingleNodeLauncher(),
queue='workq',
scheduler_options=user_opts['polaris']['scheduler_options'],
# Command to be run before starting a worker, such as:
# 'module load Anaconda; source activate parsl_env'.
worker_init=user_opts['polaris']['worker_init'],
cpus_per_node=32,
walltime='01:00:00',
nodes_per_block=1,
init_blocks=0,
min_blocks=0,
max_blocks=1,
),
)
], )
# fmt: on
config = Config(
executors=[
HighThroughputExecutor(
worker_debug=False,
address=address_by_interface('bond0.144'),
provider=SlurmProvider(
partition='GPU', # Partition / QOS
# We request all hyperthreads on a node.
launcher=SrunLauncher(overrides='-c 272'),
# string to prepend to #SBATCH blocks in the submit
# script to the scheduler eg: '#SBATCH --constraint=gpu'
scheduler_options=user_opts['perlmutter']['scheduler_options'],
# Command to be run before starting a worker, such as:
# 'module load Anaconda; source activate parsl_env'.
worker_init=user_opts['perlmutter']['worker_init'],
# Slurm scheduler on Cori can be slow at times,
# increase the command timeouts
cmd_timeout=120,
# Scale between 0-1 blocks with 2 nodes per block
nodes_per_block=2,
init_blocks=0,
min_blocks=0,
max_blocks=1,
# Hold blocks for 10 minutes
walltime='00:10:00',
),
),
],
)
