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GPU Job Scheduler Design
A GPU scheduler decides which jobs run, where they run and when resources can be reclaimed. Its placement rules must account for whole jobs, topology and tenant policy.
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Kubernetes, Slurm & GPU SchedulingDesign a job queue for 100k GPU jobs with preemption: what state, what ordering, and what happens when a quota owner returns?→Kubernetes, Slurm & GPU SchedulingDesign a GPU-aware scheduler that supports fractional GPUs: what isolation does each fraction get, and where does it break?→Coding for InfraPlace GPU jobs onto nodes. Compare first fit, best fit and worst fit, and say which one a training cluster wants.→AI Infrastructure System DesignDesign a job scheduler for 100,000 jobs on a shared GPU cluster, with preemption and checkpointing. Show me the state machine.→Coding for InfraImplement a scheduler that admits jobs by priority and preempts lower-priority work when it must. What are the rules?→Kubernetes, Slurm & GPU SchedulingOur cluster is 85% allocated but 64-GPU jobs wait for hours. Explain the fragmentation and what a scheduler should do about it.→
