Slurm
Description
HiPerGator and most other supercomputers are not used the same way as personal desktops/laptops/workstations. The massive amount of computing power requires a sophisticated approach to scheduling workloads to make sure that hardware resources are used efficiently, allocation limits are honored, and users and groups have a fair chance of using the resources without interfering with each other. Software called a resource manager and a scheduler are required to fulfill the above and other functions and conditions. on HiPerGator we use Slurm for managing hardware resources and scheduling workloads whether those submitted directly to the scheduler via job scripts or behind the scenes of more convenient interfaces like Open OnDemand, Galaxy, or JupyterHub.
Slurm is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small Linux clusters. Slurm requires no kernel modifications for its operation and is relatively self-contained. As a cluster workload manager, Slurm has three key functions. First, it allocates exclusive and/or non-exclusive access to resources (compute nodes) to users for some duration of time so they can perform work. Second, it provides a framework for starting, executing, and monitoring work (normally a parallel job) on the set of allocated nodes. Finally, it arbitrates contention for resources by managing a queue of pending work. Optional plugins can be used for accounting, advanced reservation, gang scheduling (time sharing for parallel jobs), backfill scheduling, topology optimized resource selection, resource limits by user or bank account, and sophisticated multifactor job prioritization algorithms.
Slurm Examples
For a list of sample Slurm scripts, please Sample SLURM scripts
Passing variables into a job at submission
It is possible to pass variables into a SLURM job when you submit the job using the --export flag. For example to pass the value of the variables A and b into the job script named jobscript.sbatch you can use:
sbatch --export=A=5,b='test' jobscript.sbatch
or
sbatch --export=ALL,A=4,b='test' jobscript.sbatch
The first example will replace the user's environment with a new environment containing only values for A and b and the SLURM_* environment variables. The second will add the values for A and b to the existing environment.
Using variables to set SLURM job name and output files
SLURM does not support using variables in the #SBATCH lines within a job script. However, values passed from the command line have precedence over values defined in the job script. So the job name and output/error files can be passed on the sbatch command line:
A=5 b='test' sbatch --job-name=$A.$b.run --output=$A.$b.out --export=A=$A,b=$b jobscript.sbatch