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exposing job cpus and gpus #119

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exposing job cpus and gpus
luccabb Oct 8, 2025
d50fc4c
Merge branch 'main' of github.com:facebookresearch/clusterscope into …
luccabb Oct 8, 2025
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19 changes: 19 additions & 0 deletions clusterscope/job_info.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,8 @@

from functools import lru_cache

from clusterscope.cluster_info import LocalNodeInfo

MIN_MASTER_PORT, MAX_MASTER_PORT = (20_000, 60_000)


Expand Down Expand Up @@ -40,6 +42,23 @@ def __init__(self):
self.world_size = self.get_world_size()
self.is_rank_zero = self.get_is_rank_zero()

@lru_cache(maxsize=1)
def get_cpus(self) -> int:
if self.is_slurm_job():
return int(os.environ.get("SLURM_CPUS_ON_NODE", 1))
return int(max(os.cpu_count() or 0, 1))

@lru_cache(maxsize=1)
def get_gpus(self) -> int:
if self.is_slurm_job():
return int(os.environ.get("SLURM_GPUS_ON_NODE", 1))
return sum(
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What is the intent of the ask?

Is it to know how many GPUs/CPUs are "present" on the node or "allocated" to this job?

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allocated to the job if slurm job, otherwise what's present in the node

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If I may, I think we should stick to a clear and limited contract for an API - If we want to return GPUs allocated to a job for a given API let's stick to that. I don't see benefits in either allocated or provisioned GPU count coming via the same API.

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@luccabb luccabb Oct 25, 2025 •
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@skalyan I think this is fine for now, it matches how other methods from this class behaves. I'm up to change position here as we see how it gets used

[
int(count)
for gpu, count in LocalNodeInfo().get_gpu_generation_and_count().items()
]
)

@lru_cache(maxsize=1)
def get_job_id(self) -> int:
if self.is_slurm_job():
Expand Down