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Overview

SLURM

The new HPC system, Puma, uses SLURM as a job scheduler rather than PBS Pro. SLURM has several advantages:

• It provides more robust support for a larger number of jobs in queue.
• It is used by national HPC groups (XSEDE and TACC) making it easier for users to scale out to those systems.
• It will reject jobs asking for impossible resource configurations.

Allocations and Job Queues

Using Puma with SLURM is similar to using ElGato and Ocelote with PBS. Users will still receive a monthly allocation of cpu hours associated with their PI's group which will be deducted when they run their jobs in standard. Users will also still be able to use windfall to run jobs without consuming their monthly allocations. As on Ocelote and Puma, jobs run using windfall will still be subject to preemption when resources are requested by higher-priority jobs.

Modules and Software

The process of finding, loading, and using software as modules will not change on the new system. Users will still be able to utilize the standard commands described in the Software section in our User Guide. However, in a departure from our previous systems, modules will not be available to load and utilize on the login nodes. To load, use, and test software for job submissions, users will need to request an interactive session. Interactive sessions may be requested by simply using the command "interactive". 

PBS → SLURM Rosetta Stone

In general, SLURM can translate and execute scripts written for PBS. This means that if you submit a PBS script written for Ocelote or ElGato on Puma (with the necessary resource request modifications), your script will likely run. However, there are a few caveats that should be noted:

• You will need to submit your job with the new SLURM commands, e.g. sbatch instead of qsub
• There may be some PBS directives that do not directly translate to SLURM which cannot be interpreted
• The environment variables specific to PBS and SLURM are different. If your job relies on these, you will need to update them. Common examples are PBS_O_WORKDIR and PBS_ARRAY_INDEX

To help with the transition to SLURM, we've also installed software that converts some basic PBS Pro commands into SLURM commands automatically called pbs2slurm.

To get acquainted with the new scheduling system, refer to the following list of common PBS commands, directives, and environment variables and their SLURM counterparts.

Job Examples

Single serial job submission

#!/bin/bash
#PBS -N Sample_PBS_Job
#PBS -l select=1:ncpus=1:mem=1gb
#PBS -l walltime=00:01:00
#PBS -q windfall
#PBS -W group_list=<group_name>


cd $PBS_O_WORKDIR
pwd; hostname; date

module load python
python --version

#!/bin/bash
#SBATCH --job-name=Sample_Slurm_Job
#SBATCH --ntasks=1              
#SBATCH --mem=1gb                     
#SBATCH --time=00:01:00    
#SBATCH --partition=windfall
#SBATCH --account=<group_name>    

cd $SLURM_WORKSUBMIT_DIR
pwd; hostname; date

module load python
python --version

Array Submission

IMPORTANT:

When submitting named jobs (i.e. with the line #SBATCH job-name=JobName) as arrays, SLURM will overwrite the output file with the output of the last item in the array. Use one of the following SLURM directives in your script to prevent this behavior:

1. Differentiates output file by array index. Similar to PBS default

   Code Block
   #SBATCH --output=JobName-%a.out

   
   

2. Appends the output from all tasks in an array to the same output file. Warning: if a file exists with the output name prior to running your job, the output will be appended to that file

   Code Block
   #SBATCH --open-mode=append

   
   

#!/bin/bash
#PBS -N Sample_PBS_Job
#PBS -l select=1:ncpus=1:mem=1gb
#PBS -l walltime=00:01:00
#PBS -q windfall
#PBS -W group_list=<group_name>
#PBS -J 1-5


cd $PBS_O_WORKDIR
pwd; hostname; date

echo "./sample_command input_file_${PBS_ARRAY_INDEX}.in"
 

#!/bin/bash
#SBATCH --output=Sample_SLURM_Job-%a.out
#SBATCH --ntasks=1              
#SBATCH --mem=1gb                     
#SBATCH --time=00:01:00    
#SBATCH --partition=windfall
#SBATCH --account=<group_name>    
#SBATCH --array 1-5

cd $SLURM_WORKSUBMIT_DIR
pwd; hostname; date

echo "./sample_command input_file_${SLURM_ARRAY_TASK_ID}.in"

MPI Example

#!/bin/bash
#PBS —N Sample_MPI_Job
#PBS -l select=1:ncpus=16:mem=16gb
#PBS -l walltime=00:10:00
#PBS -W group_list=<group_name>
#PBS -q standard






cd $PBS_O_WORKDIR
pwd; hostname; date
module swap openmpi mpich
/usr/bin/time -o mpit_prog.timing mpirun -np 16 a.out

#!/bin/bash
#SBATCH —job-name=Sample_MPI_Job
#SBATCH --ntasks=16
#SBATCH --ntasks-per-node=16
#SBATCH --nodes=1
#SBATCH --mem-per-cpu=1gb
#SBATCH --time=00:10:00
#SBATCH --account=<group_name>
#SBATCH --partition=standard
#SBATCH --output=Sample_MPI_Job_%A.out
#SBATCH --error=Sample_MPI_Job_%A.err

cd $SLURM_WORKSUBMIT_DIR
pwd; hostname; date
module swap openmpi3 mpich/3.3.1
/usr/bin/time -o mpit_prog.timing mpirun -np 16 a.out

rosetta_min.pdf