HPC, Slurm, and High-Performance Storage — Feeding GPUs Without Starving Them¶
Every job posting that lists "HPC experience" alongside "cloud-native" means this chapter: a shared cluster of GPU nodes behind a batch scheduler, a parallel filesystem underneath that has to keep up with hundreds of GPUs reading training data at once, and a vocabulary — partitions, QOS, fairshare, striping — that a Kubernetes background does not hand you for free. This chapter builds the HPC side of the platform from first principles: the anatomy of a cluster built around login nodes, compute nodes, and a scheduler that arbitrates them; Slurm's own architecture and the commands you actually type; and the storage layer that decides whether your expensive GPUs compute or wait. …
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