Running Jobs on RCC Systems Using the Slurm Workload Manager

Research Computing Center

Running Jobs on RCC Systems Using the Slurm Workload Manager and Best Practices

RCC users have the option to run jobs either interactively or by submitting them to be scheduled on allocated resources by the workload manager. This involves specifying parameters such as wall clock time, memory, number of CPU-cores, GPUs, etc. SLURM, which stands for Simple Linux Utility for Resource Management, and more commonly referred to as Slurm, is utilized by RCC to handle workloads on its compute clusters: Midway for open science and MidwayR for restricted systems.This workshop aims to provide users with a thorough understanding of all the compute partitions available at the RCC for job submission. Attendees will learn how to configure a Slurm job, use Slurm commands, submit jobs, and avoid common mistakes that can result in long queue times or job failures. Additionally, the workshop will cover best practices to optimize job performance and resource utilization.Participants will:<ul><li>Learn about the various Midway resources and partitions for running jobs.</li><li>Create a Slurm batch script and submit batch jobs.</li><li>Gain proficiency in the RCC module system and runtime environments for submitting serial, single, and parallel (OpenMP and MPI) jobs.</li><li>Utilize Slurm job arrays for executing jobs running with varying initial parameter values.</li><li>Efficiently pack and schedule independent processes within a Slurm job allocation</li><li>Submit message passing parallel jobs, (e.g., MPI), multi-threading, (e.g., OpenMP), and hybrid jobs.</li><li>Request Slurm interactive sessions.</li><li>Acquire familiarity with best practices and debugging techniques for Slurm scripts.</li></ul> Level: IntroductoryDuration: 1.5 hoursPrerequisites: None

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Running Jobs on RCC Systems Using the Slurm Workload Manager

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Running Jobs on RCC Systems Using the Slurm Workload Manager

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