Slurm

HPC clusters run job schedulers to distribute and manage computational resources. Generally, schedulers:

• Manage and enforce resource constraints, such as execution time, number of CPU cores, and amount of RAM a job may use;
• Provide tools for efficient communication between nodes during parallel workflows;
• Fairly coordinate the order and priority of job execution between users;
• Monitor the status and utilization of nodes.

Franklin uses Slurm as its job scheduler. A central controller runs on one of the file servers, which users submit jobs to from the access node using the srun and sbatch commands. The controller then determines a priority for the job based on the resources requested and schedules it on the queue. Priority calculation can be complex, but the overall goal of the scheduler is to optimize a tradeoff between throughput on the cluster as a whole and turnaround time on jobs.

The Jobs section describes how to submit and manage jobs with Slurm. The Queueing section describes Franklin's queuing policy and structure. The Status section details how to use Slurm to monitor the status of the cluster as whole.