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I understand that both Slurm and Kubeflow/K8s are workload manager. we wanted to leverage features of slurm parallelism etc., and use with Kubeflow or Kubernetes for ML workflow, is it possible? can they coexist or work together?

Example: We want to submit training job from Kubeflow notebook, it should work with Slrum partition to create a queue or schedule a job, if no GPU available, job should be in pending and run once the resource available?

Leverage Slrum + I understand that both Slurm and Kubeflow/K8s are workload manager.

Rajesh Muthu
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  • While Stack Overflow does permit certain questions about Kubernetes, we require that they (like all questions asked here) be specifically related to programming. This question does not appear to be specifically related to programming, which makes it off-topic here. – Turing85 Mar 03 '23 at 23:18

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