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import logging
import multiprocessing
import os
import pickle
import queue
import subprocess
from enum import Enum
from typing import Dict, List
from parsl.multiprocessing import SpawnContext
from parsl.serialize import pack_res_spec_apply_message, unpack_res_spec_apply_message
logger = logging.getLogger(__name__)
class Scheduler(Enum):
Unknown = 0
Slurm = 1
PBS = 2
def get_slurm_hosts_list() -> List[str]:
"""Get list of slurm hosts from scontrol"""
cmd = "scontrol show hostname $SLURM_NODELIST"
b_output = subprocess.check_output(
cmd, stderr=subprocess.STDOUT, shell=True
) # bytes
output = b_output.decode().strip().split()
return output
def get_pbs_hosts_list() -> List[str]:
"""Get list of PBS hosts from envvar: PBS_NODEFILE"""
nodefile_name = os.environ["PBS_NODEFILE"]
with open(nodefile_name) as f:
return [line.strip() for line in f.readlines()]
def get_nodes_in_batchjob(scheduler: Scheduler) -> List[str]:
"""Get nodelist from all supported schedulers"""
nodelist = []
if scheduler == Scheduler.Slurm:
nodelist = get_slurm_hosts_list()
elif scheduler == Scheduler.PBS:
nodelist = get_pbs_hosts_list()
else:
raise RuntimeError(f"mpi_mode does not support scheduler:{scheduler}")
return nodelist
def identify_scheduler() -> Scheduler:
"""Use envvars to determine batch scheduler"""
if os.environ.get("SLURM_NODELIST"):
return Scheduler.Slurm
elif os.environ.get("PBS_NODEFILE"):
return Scheduler.PBS
else:
return Scheduler.Unknown
class MPINodesUnavailable(Exception):
"""Raised if there are no free nodes available for an MPI request"""
def __init__(self, requested: int, available: int):
self.requested = requested
self.available = available
def __str__(self):
return f"MPINodesUnavailable(requested={self.requested} available={self.available})"
class TaskScheduler:
"""Default TaskScheduler that does no taskscheduling
This class simply acts as an abstraction over the task_q and result_q
that can be extended to implement more complex task scheduling logic
"""
def __init__(
self,
pending_task_q: multiprocessing.Queue,
pending_result_q: multiprocessing.Queue,
):
self.pending_task_q = pending_task_q
self.pending_result_q = pending_result_q
def put_task(self, task) -> None:
return self.pending_task_q.put(task)
def get_result(self, block: bool, timeout: float):
return self.pending_result_q.get(block, timeout=timeout)
class MPITaskScheduler(TaskScheduler):
"""Extends TaskScheduler to schedule MPI functions over provisioned nodes
The MPITaskScheduler runs on a Manager on the lead node of a batch job, as
such it is expected to control task placement over this single batch job.
The MPITaskScheduler adds the following functionality:
1) Determine list of nodes attached to current batch job
2) put_task for execution onto workers:
a) if resources are available attach resource list
b) if unavailable place tasks into backlog
3) get_result will fetch a result and relinquish nodes,
and attempt to schedule tasks in backlog if any.
"""
def __init__(
self,
pending_task_q: multiprocessing.Queue,
pending_result_q: multiprocessing.Queue,
):
super().__init__(pending_task_q, pending_result_q)
self.scheduler = identify_scheduler()
# PriorityQueue is threadsafe
self._backlog_queue: queue.PriorityQueue = queue.PriorityQueue()
self._map_tasks_to_nodes: Dict[str, List[str]] = {}
self.available_nodes = get_nodes_in_batchjob(self.scheduler)
self._free_node_counter = SpawnContext.Value("i", len(self.available_nodes))
# mp.Value has issues with mypy
# issue https://github.com/python/typeshed/issues/8799
# from mypy 0.981 onwards
self.nodes_q: queue.Queue = queue.Queue()
for node in self.available_nodes:
self.nodes_q.put(node)
logger.info(
f"Starting MPITaskScheduler with {len(self.available_nodes)}"
)
def _get_nodes(self, num_nodes: int) -> List[str]:
"""Thread safe method to acquire num_nodes from free resources
Raises: MPINodesUnavailable if there aren't enough resources
Returns: List of nodenames:str
"""
logger.debug(
f"Requesting : {num_nodes=} we have {self._free_node_counter}"
)
acquired_nodes = []
with self._free_node_counter.get_lock():
if num_nodes <= self._free_node_counter.value: # type: ignore[attr-defined]
self._free_node_counter.value -= num_nodes # type: ignore[attr-defined]
else:
raise MPINodesUnavailable(
requested=num_nodes, available=self._free_node_counter.value # type: ignore[attr-defined]
)
for i in range(num_nodes):
node = self.nodes_q.get()
acquired_nodes.append(node)
return acquired_nodes
def _return_nodes(self, nodes: List[str]) -> None:
"""Threadsafe method to return a list of nodes"""
for node in nodes:
self.nodes_q.put(node)
with self._free_node_counter.get_lock():
self._free_node_counter.value += len(nodes) # type: ignore[attr-defined]
def put_task(self, task_package: dict):
"""Schedule task if resources are available otherwise backlog the task"""
user_ns = locals()
user_ns.update({"__builtins__": __builtins__})
_f, _args, _kwargs, resource_spec = unpack_res_spec_apply_message(task_package["buffer"])
nodes_needed = resource_spec.get("num_nodes")
if nodes_needed:
try:
allocated_nodes = self._get_nodes(nodes_needed)
except MPINodesUnavailable:
logger.warning("Not enough resources, placing task into backlog")
self._backlog_queue.put((nodes_needed, task_package))
return
else:
resource_spec["MPI_NODELIST"] = ",".join(allocated_nodes)
self._map_tasks_to_nodes[task_package["task_id"]] = allocated_nodes
buffer = pack_res_spec_apply_message(_f, _args, _kwargs, resource_spec)
task_package["buffer"] = buffer
task_package["resource_spec"] = resource_spec
self.pending_task_q.put(task_package)
def _schedule_backlog_tasks(self):
"""Attempt to schedule backlogged tasks"""
try:
_nodes_requested, task_package = self._backlog_queue.get(block=False)
self.put_task(task_package)
except queue.Empty:
return
else:
# Keep attempting to schedule tasks till we are out of resources
self._schedule_backlog_tasks()
def get_result(self, block: bool, timeout: float):
"""Return result and relinquish provisioned nodes"""
result_pkl = self.pending_result_q.get(block, timeout=timeout)
result_dict = pickle.loads(result_pkl)
# TODO (wardlt): If the task did not request nodes, it won't be in `self._map_tasks_to_nodes`.
# Causes Parsl to hang. See Issue #3427
if result_dict["type"] == "result":
task_id = result_dict["task_id"]
assert task_id in self._map_tasks_to_nodes, "You are about to experience issue #3427"
nodes_to_reallocate = self._map_tasks_to_nodes[task_id]
self._return_nodes(nodes_to_reallocate)
self._schedule_backlog_tasks()
return result_pkl
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