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Updated schedule logic for placement groups for ray backend #2523

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merged 9 commits into from
Sep 20, 2022
Merged

Updated schedule logic for placement groups for ray backend #2523

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19b3d97
updated scheduling logic for resource isolation
magdyksaleh Sep 18, 2022
ef061fd
fixes
magdyksaleh Sep 18, 2022
c47f129
fixes
magdyksaleh Sep 18, 2022
0b12bbf
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Sep 18, 2022
1cb1cb2
Merge branch 'updated-schedule-logic-for-pg' of github.com:ludwig-ai/…
magdyksaleh Sep 18, 2022
fd5e2ad
Add test and clean up remove_pg logic
magdyksaleh Sep 19, 2022
b04a4ed
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Sep 19, 2022
19ba636
fix test
magdyksaleh Sep 19, 2022
e86d46e
fix test2
magdyksaleh Sep 19, 2022
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16 changes: 15 additions & 1 deletion ludwig/backend/ray.py
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Original file line number Diff line number Diff line change
Expand Up @@ -812,6 +812,18 @@ def initialize(self):
# Disable placement groups on dask
dask.config.set(annotations={"ray_remote_args": {"placement_group": None}})

def generate_bundles(self, num_cpu):
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Nit: prefix with underscore since this is not really meant to be used outside this package.

# Ray requires that each bundle be scheduleable on a single node.
# So a bundle of 320 cpus would never get scheduled. For now a simple heuristic
# to be used is to just request cpus 4 at a time.
if num_cpu <= 4:
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bundles = [{"CPU": num_cpu}]
else:
bundles = [{"CPU": 4} for _ in range(int(num_cpu // 4))]
if num_cpu % 4:
bundles.append({"CPU": num_cpu % 4})
return bundles

@contextlib.contextmanager
def provision_preprocessing_workers(self):
if not self._preprocessor_kwargs.get("use_preprocessing_placement_group", False):
Expand All @@ -822,7 +834,9 @@ def provision_preprocessing_workers(self):
yield
else:
num_cpu = self._preprocessor_kwargs["num_cpu_workers"]
self._preprocessor_pg = placement_group([{"CPU": num_cpu}])
bundles = self.generate_bundles(num_cpu)
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logger.info("Requesting bundles of %s for preprocessing", bundles)
self._preprocessor_pg = placement_group(bundles)
ready = self._preprocessor_pg.wait(FIFTEEN_MINS_IN_S)

if not ready:
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