Support submit sleep in scheduler

src/ert/config/queue_config.py

@@ -32,6 +32,7 @@
 class QueueConfig:
     job_script: str = shutil.which("job_dispatch.py") or "job_dispatch.py"
     max_submit: int = 2
+    submit_sleep: float = 0.0
     queue_system: QueueSystem = QueueSystem.LOCAL
     queue_options: Dict[QueueSystem, List[Tuple[str, str]]] = field(
         default_factory=dict
@@ -48,6 +49,7 @@ def from_dict(cls, config_dict: ConfigDict) -> QueueConfig:
         )
         job_script = job_script or "job_dispatch.py"
         max_submit: int = config_dict.get("MAX_SUBMIT", 2)
+        submit_sleep: float = config_dict.get("SUBMIT_SLEEP", 0.0)
         queue_options: Dict[QueueSystem, List[Tuple[str, str]]] = defaultdict(list)
         for queue_system, option_name, *values in config_dict.get("QUEUE_OPTION", []):
             if option_name not in VALID_QUEUE_OPTIONS[queue_system]:
@@ -67,6 +69,12 @@ def from_dict(cls, config_dict: ConfigDict) -> QueueConfig:
                     " usually provided by the site-configuration file, beware that"
                     " you are effectively replacing the default value provided."
                 )
+            if (
+                values
+                and option_name == "SUBMIT_SLEEP"
+                and selected_queue_system == queue_system
+            ):
+                submit_sleep = float(values[0])
 
         for queue_system_val in queue_options:
             if queue_options[queue_system_val]:
@@ -85,12 +93,15 @@ def from_dict(cls, config_dict: ConfigDict) -> QueueConfig:
                 queue_options[selected_queue_system],
             )
 
-        return QueueConfig(job_script, max_submit, selected_queue_system, queue_options)
+        return QueueConfig(
+            job_script, max_submit, submit_sleep, selected_queue_system, queue_options
+        )
 
     def create_local_copy(self) -> QueueConfig:
         return QueueConfig(
             self.job_script,
             self.max_submit,
+            self.submit_sleep,
             QueueSystem.LOCAL,
             self.queue_options,
         )

src/ert/ensemble_evaluator/_builder/_legacy.py

@@ -202,6 +202,7 @@ async def _evaluate_inner(  # pylint: disable=too-many-branches
                     self.active_reals,
                     max_submit=self._queue_config.max_submit,
                     max_running=self._queue_config.max_running,
+                    submit_sleep=self._queue_config.submit_sleep,
                     ens_id=self.id_,
                     ee_uri=self._config.dispatch_uri,
                     ee_cert=self._config.cert,

src/ert/scheduler/job.py

@@ -92,6 +92,8 @@ async def _submit_and_run_once(self, sem: asyncio.BoundedSemaphore) -> None:
         timeout_task: Optional[asyncio.Task[None]] = None
 
         try:
+            if self._scheduler.submit_sleep_state:
+                await self._scheduler.submit_sleep_state.sleep_until_we_can_submit()
             await self._send(State.SUBMITTING)
             await self.driver.submit(
                 self.real.iens, self.real.job_script, cwd=self.real.run_arg.runpath

src/ert/scheduler/scheduler.py

@@ -5,6 +5,7 @@
 import logging
 import os
 import ssl
+import time
 from collections import defaultdict
 from dataclasses import asdict
 from pathlib import Path
@@ -39,6 +40,23 @@ class _JobsJson:
     experiment_id: Optional[str]
 
 
+class SubmitSleeper:
+    _submit_sleep: float
+    _last_started: float
+
+    def __init__(self, submit_sleep: float):
+        self._submit_sleep = submit_sleep
+        self._last_started = (
+            time.time() - submit_sleep
+        )  # Allow the first to start immediately
+
+    async def sleep_until_we_can_submit(self) -> None:
+        now = time.time()
+        next_start_time = max(self._last_started + self._submit_sleep, now)
+        self._last_started = next_start_time
+        await asyncio.sleep(max(0, next_start_time - now))
+
+
 class Scheduler:
     def __init__(
         self,
@@ -47,6 +65,7 @@ def __init__(
         *,
         max_submit: int = 1,
         max_running: int = 1,
+        submit_sleep: float = 0.0,
         ens_id: Optional[str] = None,
         ee_uri: Optional[str] = None,
         ee_cert: Optional[str] = None,
@@ -57,6 +76,10 @@ def __init__(
         self.driver = driver
         self._tasks: MutableMapping[int, asyncio.Task[None]] = {}
 
+        self.submit_sleep_state: Optional[SubmitSleeper] = None
+        if submit_sleep > 0:
+            self.submit_sleep_state = SubmitSleeper(submit_sleep)
+
         self._jobs: MutableMapping[int, Job] = {
             real.iens: Job(self, real) for real in (realizations or [])
         }

tests/unit_tests/scheduler/test_scheduler.py

@@ -1,6 +1,8 @@
 import asyncio
 import json
+import random
 import shutil
+import time
 from pathlib import Path
 from typing import List
 
@@ -342,3 +344,91 @@ async def wait(iens):
 
     assert await sch.execute(min_required_realizations=5) == EVTYPE_ENSEMBLE_STOPPED
     assert killed_iens == [6, 7, 8, 9]
+
+
+@pytest.mark.parametrize(
+    "submit_sleep, iens_stride, realization_runtime",
+    [(0, 1, 0.1), (0.1, 1, 0.1), (0.1, 1, 0), (0.1, 2, 0)],
+)
+async def test_submit_sleep(
+    submit_sleep,
+    iens_stride,  # Gives sparse ensembles when > 1
+    realization_runtime,
+    storage,
+    tmp_path,
+    mock_driver,
+):
+    run_start_times: List[float] = []
+
+    async def wait():
+        nonlocal run_start_times
+        run_start_times.append(time.time())
+        await asyncio.sleep(realization_runtime)
+
+    ensemble_size = 10
+
+    ensemble = storage.create_experiment().create_ensemble(
+        name="foo", ensemble_size=ensemble_size * iens_stride
+    )
+    realizations = [
+        create_stub_realization(ensemble, tmp_path, iens * iens_stride)
+        for iens in range(ensemble_size)
+    ]
+
+    sch = scheduler.Scheduler(
+        mock_driver(wait=wait), realizations, submit_sleep=submit_sleep, max_running=0
+    )
+    await sch.execute()
+
+    deltas = [
+        next_start - start
+        for start, next_start in zip(run_start_times[:-1], run_start_times[1:])
+    ]
+    assert min(deltas) >= submit_sleep * 0.8
+    assert max(deltas) <= submit_sleep + 0.1
+
+
+@pytest.mark.parametrize(
+    "submit_sleep, realization_max_runtime, max_running",
+    [
+        (0.01, 0.01, 1),
+        (0.01, 0.01, 10),
+        (0.01, 0.1, 5),
+    ],
+)
+async def test_submit_sleep_with_max_running(
+    submit_sleep, realization_max_runtime, max_running, storage, tmp_path, mock_driver
+):
+    run_start_times: List[float] = []
+
+    async def wait():
+        nonlocal run_start_times
+        run_start_times.append(time.time())
+        # If the realization runtimes are constant, we will never get into
+        # the situation where we can start many realizations at the same moment
+        runtime = realization_max_runtime * random.random()
+        await asyncio.sleep(runtime)
+
+    ensemble_size = 10
+
+    ensemble = storage.create_experiment().create_ensemble(
+        name="foo", ensemble_size=ensemble_size
+    )
+    realizations = [
+        create_stub_realization(ensemble, tmp_path, iens)
+        for iens in range(ensemble_size)
+    ]
+
+    sch = scheduler.Scheduler(
+        mock_driver(wait=wait),
+        realizations,
+        submit_sleep=submit_sleep,
+        max_running=max_running,
+    )
+    await sch.execute()
+
+    deltas = [
+        next_start - start
+        for start, next_start in zip(run_start_times[:-1], run_start_times[1:])
+    ]
+    assert min(deltas) >= submit_sleep * 0.8