Hello Everyone, We Have Clearml (Free Version) Deployed On Gke. We Are Using Agents To Work With Gpu Nodes On The Gke. When We Start A Task On Gpu Worker, The Scalars Show'S That The Task Is Trying To Use The Entire Gpu'S On The Node (We Have 8 ) Even Th

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Hello everyone,
We have ClearML (free version) deployed on GKE.
We are using agents to work with GPU nodes on the GKE.

When we start a task on GPU worker, the scalars show's that the task is trying to use the entire GPU's on the node (we have 8 ) even though we limit the worker to use only 1 gpu at the time so we can have 8 runs in parallel.

Is there any resource or config we need to set in order to inform ClearML that it should only refer to the GPU's the worker has requested?

  				
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	2 months ago

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					JitteryCrab82
				
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not sure about that in special, but take a look at the doc config: None
sometimes is difficult to understand the priority of the configs ( ENV_CONFIG, server yml, agent yml, etc.. ) because you can set a config by the agent config but the ENV is overwriting the config.

  				
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	2 months ago

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					ThoughtlessTiger0
				
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It was related to the deployment having privileged permission enabled, after disabling it was fine.

Thanks

  				
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	2 months ago

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					JitteryCrab82
				
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