SLURM is a queue management system and stands for Simple Linux Utility for Resource Management. SLURM was developed at the Lawrence Livermore National Lab and currently runs some of the largest compute clusters in the world. SLURM is the primary job manager on Cheaha (BigGreen- new hardware) while GridEngine continues to be the job manager on the old hardware.
SLURM is similar in many ways to GridEngine or most other queue systems. You write a batch script then submit it to the queue manager (scheduler). The queue manager then schedules your job to run on the queue (or partition in SLURM parlance) that you designate. Below we will provide an outline of how to submit jobs to SLURM, how SLURM decides when to schedule your job and how to monitor progress.
General SLURM Documentation
The primary source for documentation on SLURM usage and commands can be found at the SLURM site. If you Google for SLURM questions, you'll often see the Lawrence Livermore pages as the top hits, but these tend to be outdated.
A great way to get details on the SLURM commands is the man pages available from the Cheaha cluster. For example, if you type the following command:
you'll get the manual page for the sbatch command.
Logging on and Running Jobs from the command line
Cheaha (new hardware) run the CentOS 7 version of the Linux operating system and commands are run under the "bash" shell. There are a number of Linux and bash references, cheat sheets and tutorials available on the web.
- Stage data to $USER_SCRATCH (your scratch directory)
- Research how to run your code in "batch" mode. Batch mode typically means the ability to run it from the command line without requiring any interaction from the user.
- Identify the appropriate resources needed to run the job. The following are mandatory resource requests for all jobs on Cheaha
- Number of processor cores required by the job
- Maximum memory (RAM) required per core
- Maximum runtime
- Write a job script specifying queuing system parameters, resource requests and commands to run program
- Submit script to queuing system (sbatch script.job)
- Monitor job (squeue)
- Review the results and resubmit as necessary
- Clean up the scratch directory by moving or deleting the data off of the cluster