You are managing a deep learning workload on a Slurm cluster with multiple GPU nodes,...

NVIDIA NCP-AIO Question Answer

You are managing a deep learning workload on a Slurm cluster with multiple GPU nodes, but you notice that jobs requesting multiple GPUs are waiting for long periods even though there are available resources on some nodes.

How would you optimize job scheduling for multi-GPU workloads?

Reduce memory allocation per job so more jobs can run concurrently, freeing up resources faster for multi-GPU workloads.

Ensure that job scripts use --gres=gpu: and configure Slurm’s backfill scheduler to prioritize multi-GPU jobs efficiently.

Set up separate partitions for single-GPU and multi-GPU jobs to avoid resource conflicts between them.

Increase time limits for smaller jobs so they don’t interfere with multi-GPU job scheduling.

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NVIDIA NCP-AIO Summary

Vendor: NVIDIA
Product: NCP-AIO
Update on: Jul 22, 2025
Questions: 66

Price: $52.5 ~~$149.99~~

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You are managing a deep learning workload on a Slurm cluster with multiple GPU nodes,...

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