HPC batch schedulers (Slurm and successors)
BOTTLENECKSchedMD's Slurm dominates academic clusters but cannot scale elastically, forcing reliance on rigid queue-based architectures.
Queue-based batch systems like Slurm, inherited from supercomputing, still rule academic and national-lab training clusters. They handle large-node jobs and priority queues well but cannot scale elastically like cloud-native tools. SchedMD and HPC integrators earn licensing and support revenue.
Queue-based workload managers from the HPC tradition, dominant in large-scale training and research clusters.
What the evidence shows
Many places are coalescing around Slurm, making it the most popular batch scheduler.
reddit.comSlurm is now the most popular batch scheduler, but 10 years ago it was PBS/TORQUE.
mattermodeling.stackexchange.comSlurm has overtaken PBS in research and industry, leading to declining adoption of PBS.
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