1. Introduction
  2. Example of a Job Script
  3. How to Convert a Task ID to a More Useful Set of Parameters

  4. How to Consolidate Small Jobs into Fewer Larger Jobs Using Job Arrays
  5. Rules for Submitting Job Arrays that use Parallel Environments (like MPI) 

1. Introduction

A jobs array is specified by adding a task range to qsub via the -t flag:

% qsub -t 1-100 model.job

Your job-array NNNNNN.1-100:1 ("model.job") has been submitted

The scheduler will start 100 jobs, each starting the job script file model.job, and pass to each job a task identifier (a number between 1 and 100) via an environment variable.


The syntax for the -t flag is -t n[-m[:s]], namely:

-t 1-20run 20 tasks, with task IDs  ranging from1  to 20
-t 10-30run 21 tasks, with task IDs ranging from 10  to 30
-t 50-140:10run 10 tasks, with task IDs ranging from 50  to 140 by step of 10 (50, 60, ..., 140)
-t 20run one task, with task ID 20


Each instantiation of the job will have access to the following four environment variables:

SGE_TASK_IDunique ID for the specific task
SGE_TASK_FIRSTID of the first task, as specified with qsub
SGE_TASK_LASTID of the last task, as specified with qsub
SGE_TASK_STEPSIZEtask ID step size, as specified with qsub


You can also limit the number of concurrent tasks with the -tc flag, for example:

 % qsub -t 1-1000 -tc 100 model.job

will request to run 1,000 jobs, but no more than 100 running at the same time.

2. Example of a Job Script

The follow example shows how to submit a job array, using embedded directives:

# /bin/csh
#
#$ -N model-1k -cwd -j y -o model-$TASK_ID.log
#$ -t 1-1000 -tc 100
#
echo + `date` $JOB_NAME started on $HOSTNAME in $QUEUE with jobID=$JOB_ID and taskID=$SGE_TASK_ID
#
set TID = $SGE_TASK_ID
./model -id $TID
#
echo = `date` $JOB_NAME for taskID=$SGE_TASK_ID done.

This example

3. How to Convert a Task ID to a More Useful Set of Parameters

In most cases, when starting a computation you will need to convert a simple task identifier to a slew of parameters.

You can put that conversion into your code, but you may not want to do it, or can't do it because you are using some tool or package you can't modify.

Here are a few suggestions (Un*x tricks, using C-shell syntax) on how to do it:

  1. You can use a separate input file for each job (task):
    If your code reads from stdin (standard input) you can do something like this:

    @ i = $SGE_TASK_ID
    ./domodel < input.$i

    You just need to prepare as many input.NNN files as cases you want to run, from input.1 to input.500 for example.

    If you prefer to call them input.001 to input.500, you can use awk to reformat $i as follows:

    @ i = $SGE_TASK_ID
    set I = `echo $i | awk '{printf "%3.3d", $1}'`
    ./domodel < input.$I

    where "%3.3d" is the trick (a C-like format specifier) to convert the integer $i into a 3 character string $I with leading zeros if needed.

    The Bourne shell (sh or bash) equivalent is:

    i=$SGE_TASK_ID
    I=`echo $i | awk '{printf "%3.3d", $1}'`
    ./domodel < input.$I
  2. You can use a single text file that lists a slew of parameters and extract one line, using the command awk (man awk):

    @ i = $SGE_TASK_ID
    set P = (`awk "NR==$i" parameters-list.txt`)
    ./compute $P

    This example will extract one line from the file parameters-list.txt, namely the line whose line number is stored in the variable $i (the 1st line, the 2nd line, etc). [NR stands for record number]

    It sets the variable $P to the content of that one line.

    You just have to create such a file with as many lines as cases of compute you wish to run. Each line holds the parameters that will be passed to compute.

    The Bourne shell (sh or bash) equivalent is:

    i=$SGE_TASK_ID
    P=`awk "NR==$i" parameters-list.txt`
    ./compute $P


  3. You can write a tool (a small program or script, that I call here mytool) that does the conversion. You just run it to get the parameters:

    @ i = $SGE_TASK_ID
    set P = (`./mytool $i`)

    or for Bourne shell (sh or bash) aficionados: 

    i=$SGE_TASK_ID
    P=`./mytool $i`

       

  4. You can use the shell syntax to use or manipulate the variable $SGE_TASK_ID to execute the right (set of ) command(s) from the given task integer

4. How to Consolidate Small Jobs into Fewer Larger Jobs

# /bin/csh
#
# simple wrapper to consolidate using the step size
#
#$ -N model-1k20 -cwd -j y -o model-$TASK_ID-by-20.log
#$ -t 1-1000:20
#
echo + `date` $JOB_NAME started on $HOSTNAME in $QUEUE with jobID=$JOB_ID
#
@ iFr = $SGE_TASK_ID
@ iTo = $iFr + $SGE_TASK_STEPSIZE - 1
if ($iTo > $SGE_TASK_LAST) @ iTo = $SGE_TASK_LAST
#
echo running model.csh for taskIDs $iFr to $iTo
@ i = $iFr
while ($i <= $iTo)
  ./model.csh $i >& model-$i.log
  @ i++
end
#
echo = `date` $JOB_NAME for taskIDs $iFr to $iTo done.

This wrapper, that I call domodel.job, will run 20 models in a row, using the step size of the job array, via the csh script model.csh.

So instead of running 1,000 three-minute-long jobs, it will run 50 one-hour-long jobs.

You can, of course, adjust the step size accordingly, including setting it to 1 for cases when individual models lead to long computations.

The script model.csh is simply:

#!/bin/csh
#
set TID = $1
echo + `date` model.csh started for taskID=$TID
#
./model -id $TID
#
echo = `date` model.csh for taskID=$TID done.

but it can be as complex as you may need/want it to be. (BTW, there is nothing C-shell or Bourne shell syntax specific in this example)

The file model.csh must be authorized to be executed with the command:

% chmod +x model.csh

You can use a bash script, or any other valid Linux command in place of the line ./model.csh.

5. Rules for Submitting Job Arrays that use Parallel Environments (like MPI)

(warning) While one can submit a job array that uses a parallel environment (-pe and -t, or parallel job arrays), one must use a the following approach to avoid a race condition specific to SGE.

How to Write a Parallel Job Array

  1. Do not use embedded directive (sigh).

  2. Write a script (sh or csh, or...) with the needed steps, as for a job script.
  3. Make that script executable (chmod +x).
  4. Write a file with the qsub command and all the options that you would otherwise put as embedded directives.
  5. Pass the -b y option to qsub and specify the full path of the script to execute.
  6. Source that file to submit the parallel job array.
  7. (warning) Do not modify the executable script file while the job array is running.

Example

The following job script with embedded directives must be broken into two files:

one job script with embedded directivesis replaced by two files, a qsub_XXX.sou and a XXX.sh
#--------
#$ -q mThC.q
#$ -pe orte 20
#$ -l mres=4G,h_data=4G,h_vmem=4G
#$ -cwd -y j -N demo -o demo.$TASK_ID.log
#$ -t 1-100
#-------
module load some/thing
#-------
echo + `date` job $JOB_NAME started in $QUEUE with jobID=$JOB_ID on $HOSTNAME
echo + taskID=$SGE_TASK_ID
echo + NSLOTS=$NSLOTS distributed over:
cat $PE_HOSTFILE
#
mpirun -np $NSLOTS crunch -i input.$SGE_TASK_ID -o output.$SGE_TASK_ID
#
echo = `date` job $JOB_NAME done
qsub \
 -q mThC.q \
 -pe orte 20 \
 -l mres=4G,h_data=4G,h_vmem=4G \
 -cwd -y j -N demo -o 'demo.$TASK_ID.log' \
 -t 1-100 \
 -b y $PWD/demo.sh

(warning) no spaces after the '\'

#!/bin/sh
# any embedded directives here will be ignored
#-------
module load some/thing
#-------
echo + `date` job $JOB_NAME started in $QUEUE with jobID=$JOB_ID on $HOSTNAME
echo + taskID=$SGE_TASK_ID
echo + NSLOTS=$NSLOTS distributed over:
cat $PE_HOSTFILE
#
mpirun -np $NSLOTS crunch -i input.$SGE_TASK_ID -o output.$SGE_TASK_ID
#
echo = `date` job $JOB_NAME done

(lightbulb) this can be any type of executable script

Before submitting the job array, make sure the script is executable:

chmod +x demo.sh

To submit the job array, simply source the qsub_XXX.sou file:

source qsub_demo.sou

You can edit the qsub_demo.sou to submit more tasks, but do not modify the executable script file while the job array is running.

 


Last updated SGK.