Storage: local drives

See also

the storage tutorial.

Local disks on computing nodes are the preferred place for doing your IO. The general idea is use network storage as a backend and local disk for actual data processing.

  • In the beginning of the job cd to /tmp and make a unique directory for your run
  • copy needed input from WRKDIR to there
  • run your calculation normally forwarding all the output to /tmp
  • in the end copy relevant output to WRKDIR for analysis and further usage

Pros

  • You get better and steadier IO performance. WRKDIR is shared over all users making per-user performance actually rather poor.
  • You save performance for WRKDIR to those who cannot use local disks.
  • You get much better performance when using many small files (Lustre works poorly here).
  • Saves your quota if your code generate lots of data but finally you need only part of it
  • In general, it is an excellent choice for single-node runs (that is all job’s task run on the same node).

Cons

  • Not feasible for huge files (>100GB). Use WRKDIR instead.
  • Small learning curve (must copy files before and after the job).
  • Not feasible for cross-node IO (MPI jobs). Use WRKDIR instead.

How to use local drives on compute nodes

NOT for the long-term data. Cleaned every time your job is finished.

You have to use --gres=spindle to ensure that you get a hard disk (note 2019-january: except GPU nodes).

/tmp is a bind-mounted user specific directory. Directory is per-user (not per-job that is), if you get two jobs running on the same node, you get the same /tmp.

Interactively

How to use /tmp when you login interactively

$ sinteractive -t 1:00:00              # request a node for one hour
(node)$ mkdir /tmp/$SLURM_JOB_ID       # create a unique directory, here we use
(node)$ cd /tmp/$SLURM_JOB_ID
... do what you wanted ...
(node)$ cp your_files $WRKDIR/my/valuable/data  # copy what you need
(node)$ cd; rm -rf /tmp/$SLURM_JOB_ID  # clean up after yourself
(node)$ exit

In batch script

Batch job example that prevents data lost in case program gets terminated (either because of scancel or due to time limit).

#!/bin/bash

#SBATCH --time=0-12:00:00 --mem-per-cpu=2500                  # time and memory requirements

mkdir /tmp/$SLURM_JOB_ID                                      # get a directory where you will send all output from your program
cd /tmp/$SLURM_JOB_ID

## set the trap: when killed or exits abnormally you get the
## output copied to $WRKDIR/$SLURM_JOB_ID anyway
trap "mkdir $WRKDIR/$SLURM_JOB_ID; mv -f /tmp/$SLURM_JOB_ID $WRKDIR/$SLURM_JOB_ID; exit" TERM EXIT

## run the program and redirect all IO to a local drive
## assuming that you have your program and input at $WRKDIR
srun $WRKDIR/my_program $WRKDIR/input > output

mv /tmp/$SLURM_JOB_ID/output $WRKDIR/SOMEDIR                   # move your output fully or partially

Batch script for thousands input/output files

If your job requires a large amount of files as input/output using tar utility can greatly reduce the load on the $WRKDIR-filesystem.

Using methods like this is recommended if you’re working with thousands of files.

Working with tar balls is done in a following fashion:

  1. Determine if your input data can be collected into analysis-sized chunks that can be (if possible) re-used
  2. Make a tar ball out of the input data (tar cf <tar filename>.tar <input files>)
  3. At the beginning of job copy the tar ball into /tmp and untar it there (tar xf <tar filename>.tar)
  4. Do the analysis here, in the local disk
  5. If output is a large amount of files, tar them and copy them out. Otherwise write output to $WRKDIR

A sample code is below:

#!/bin/bash

#SBATCH --time=0-12:00:00 --mem-per-cpu=2000      # time and memory requirements
mkdir /tmp/$SLURM_JOB_ID                          # get a directory where you will put your data
cp $WRKDIR/input.tar /tmp/$SLURM_JOB_ID           # copy tarred input files
cd /tmp/$SLURM_JOB_ID

trap "rm -rf /tmp/$SLURM_JOB_ID; exit" TERM EXIT  # set the trap: when killed or exits abnormally you clean up your stuff

tar xf input.tar                                  # untar the files
srun  input/*                            # do the analysis, or what ever else
tar cf output.tar output/*                        # tar output
mv output.tar $WRKDIR/SOMEDIR                     # copy results back