GPU Quotas, Utilization & Chargeback On-prem
Who uses the owned GPUs and how well: allocated versus SM-active utilization, finding and reclaiming idle GPUs, quota models per team, showback versus chargeback, and building a cost per GPU-hour from depreciation, power, space and staff.
Overview
Why this topic
An owned GPU cluster costs the same whether its GPUs compute or sit idle. Teams ask for more GPUs long before the ones they hold are busy, and without numbers the loudest team wins. Quotas decide who may hold GPUs, utilization says whether they are used well, and chargeback puts a price on holding them.
> [!IMPORTANT] "Allocated" and "used" are different numbers. A cluster can be 100% allocated and 30% busy. Report both, always side by side.
Interview questions
- Leadership asks "how utilized is the GPU cluster?" What do you report, and how do you measure it?
- Design idle detection and reclaim for notebooks and long-held GPU pods.
- Five teams share 128 GPUs. Design the quota model with Kueue.
- Build a cost per GPU-hour for owned hardware that finance will accept.
- Showback or chargeback? How do you roll it out without teams gaming it?
- On a Slurm GPU cluster, how do you account, prioritize and report GPU use per group?
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