Guide
What Slurm does, and what a GPU cluster needs around it
A short primer for teams deciding how to run their first, or next, GPU cluster.
By the C-Gen.AI engineering team
What Slurm is
Slurm is an open-source workload manager for Linux clusters. It decides which job runs on which nodes and when, keeps the rest waiting in a queue and can record what every job used. Nodes are grouped into partitions that work as job queues, and plugins add accounting, limits per user or account and multifactor job priorities.
Why AI teams choose it
Distributed training needs many GPUs allocated at the same moment, on nodes that can exchange data quickly. Slurm comes from high-performance computing, where large parallel jobs like this are routine, so multi-node allocation, queues and priorities work without extra tooling. Many researchers already know it from university and national lab clusters.
What Slurm leaves to you
Slurm schedules work. It doesn’t provision cloud GPUs, install drivers, watch GPU health, serve models to users or turn accounting records into reports a finance team can read. Teams usually build those pieces themselves, around the scheduler, and then keep maintaining them.
Questions to ask before you build
How long until the first job runs? Who maintains monitoring when the person who set it up moves on? What happens when a GPU fails halfway through a multi-day run? Where will the model you just trained be served? The answers decide whether the cluster becomes a project or a platform.
