Parallel GRASS jobs

Parallel GRASS jobs

NOTE: GRASS 6 libraries are NOT thread safe (except for GPDE, see below).

Background

This you should know about GRASS' behaviour concerning multiple jobs:

• You can run multiple processes in multiple locations (what's that?). Peaceful coexistence.
• You can run multiple processes in the same mapset, but only if the region is untouched (but it's really not recommended). Better launch each job in its own mapset within the location.
• You can run multiple processes in the same location, but in different mapsets. Peaceful coexistence.

Approach

Essentially there are at least two approaches of "poor man" parallelization without modifying GRASS source code:

• split map into spatial chunks (possibly with overlap to gain smooth results)
• time series: run each map elaboration on a different node.

GPDE using OpenMP

The only parallelized library in GRASS 6.3 is GRASS Partial Differential Equations Library (GPDE). The library design is thread safe and supports threaded parallelism with OpenMP. The code is not yet widely used in GRASS. See here for details.

OpenMosix

NOTE: The openMosix Project has officially closed as of March 1, 2008.

If you want to launch several GRASS jobs in parallel, you have to launch each job in its own mapset. Be sure to indicate the mapset correctly in the GISRC file (see above). You can use the process ID (PID, get with $$ or use PBS jobname) to generate a almost unique number which you can add to the mapset name.

Now you could launch the jobs on an openMosix cluster (just install openMosix on your colleague's computers...).

PBS

Note: For PBS details, read on here.

You need essentially two scripts:

• GRASS job script (which takes the name(s) of map(s) to elaborate from environmental variables
• script to launch this GRASS-script as job for each map to elaborate

General steps (for multiple serial jobs on many CPUs):

• Job definition
  • PBS setup (in the header): define calculation time, number of nodes, number of processors, amount of RAM for individual job;
  • data are stored in centralized directory which is seen by all nodes;
• Job execution (launch of jobs)
  • user launches all jobs ("qsub"), they are submitted to the queue. Use the GRASS_BATCH_JOB variable to define the name of the elaboration script.
  • the scheduler optimizes among all user the execution of the jobs according to available resources and requested resources;
  • for the user this means that 0..max jobs are executed in parallel (unless the administrators didn't define either priority or limits). The user can then observe the job queue ("showq") to see other jobs ahead and scheduling of own jobs. Once a job is running, the cluster possibly sends a notification email to the user, the same again when a job is terminating.
  • At the end of the elaboration call a second batch job which only contains g.copy to copy the result into a common mapset. There is a low risk of race condition here in case that two nodes finish at the same time but this could be even trapped in a loop which checks if the target mapset is locked and, if needed, launches g.copy again 'till success.
• Job planning
  • The challenging part for the user is to estimate the execution time since PBS kills jobs which exceed the requested time. The same applies to the request for number of nodes and CPUs per node as well as the amount of needed RAM. Usually tests are needed to see the performance in order to impose the values correctly in the PBS script (see below).

How to write the scripts: To avoid race conditions, you can automatically generate multiple mapsets in a given location. When you start GRASS (in your script) with path to grassdata/location/mapset/ and the requested mapset does not yet exist, it will be automatically created. So, as first step in your job script, be sure to run

     g.mapsets add=mapset1_with_data[,mapset2_with_data]

to make the data which you want to elaborate accessible. You would then loop over many map names (e.g. "aqua_lst1km20020706.LST_Night_1km.filt") and launch the script with map name as first parameter:

     ------- snip (you need to update this for PBS stuff and save as 'launch_grassjob_55min.sh' -----------
     #!/bin/sh
     ### Project number, enter if applicable (needed to manage your CPU hours)
     #PBS -A HPC2N-2008-001
     #
     ### Job name - defaults to name of submit script
     #PBS -N modis_interpolation_GRASS_RST.sh
     #
     ### Output files - defaults to jobname.[eo]jobnumber
     #PBS -o modis_rst.$MYMODIS.out
     #PBS -e modis_rst.$MYMODIS.err
     #
     ### Mail on - a=abort, b=beginning, e=end - defaults to a
     #PBS -m abe
     ### Number of nodes - defaults to 1:1
     ### Requesting 1 nodes with 1 processor per node:
     #PBS -l nodes=1:ppn=1
     ### Requesting time - defaults to 30 minutes
     #PBS -l walltime=00:55:00
     ### amount of physical memory (in MB) each processor will use with a line:
     #PBS -l pvmem=3000m

     # we'll call this script below in a loop, giving the name of the map to elaborate as parameter
     MYMAPSET=$1
     TARGETMAPSET=results
     
     # define as env. variable the batch job which does the real GRASS elaboration (so, which contains the GRASS commands)
     GRASS_BATCH_JOB=/shareddisk/modis_job.sh
     grass63 -text /shareddisk/grassdata/myloc/$MYMAPSET
     
     # since we write results to a temporary mapset, copy over result to target mapset
     # this we launch again as small GRASS job
     export INMAP=${CURRMAP}_rst
     export INMAPSET=$MYMAPSET
     export OUTMAP=$INMAP
     export GRASS_BATCH_JOB=/shareddisk/gcopyjob.sh
     grass63 -text  /shareddisk/grassdata/myloc/$TARGETMAPSET
     exit 0
     ------- snap ----------

You see, that GRASS is run twice. Note that you need GRASS Version >=6.3 to make use of GRASS_BATCH_JOB (if variable is present, GRASS automatically executes that job instead of launching the normal interactive user interface).

The script 'gcopyjob.sh' simply contains:

     ------- snip -----------
     #!/bin/sh
     g.copy rast=$INMAP@$INMAPSET,$OUTMAP --o
     ------- snap ----------

Launching many jobs:

We do this by simply looping over all map names to elaborate:

     cd /shareddisk/
     # loop and launch (we just pick the names from the GRASS DB itself; here: do all maps)
     # instead of launching immediately, we create a launch script:
     for i in `find grassdata/myloc/modis_originals/cell/ -name '*'` ; do 
         NAME=`basename $i`
         echo qsub -v MYMODIS=$NAME ./launch_grassjob_55min.sh
     done | sort > launch1.sh 

     # now really launch the jobs:
     sh launch1.sh

That's it! Emails will arrive to notify upon begin, abort (hopefully not!) and end of job execution.

Grid Engine

• URL: http://gridengine.sunsource.net/ (see user docs there and here)
• Lauching jobs: qsub
• Navigating the Grid Engine System with GUI: qmon
• Job statstics: qstat

Example script to lauch Grid Engine jobs:

     #!/bin/sh

     # Serial job, MODIS LST elaboration
     # Markus Neteler, 2008

     ## GE settings
     # request Bourne shell as shell for job
     #$ -S /bin/sh
     # run in current working directory
     #$ -cwd

     # We want Grid Engine to send mail when the job begins and when it ends.
     #$ -M neteler@somewhere.it
     #$ -m abe

     # bash debug output
     set -x

     ############
     # SUBMIT from home dir to node:
     #  cd $HOME
     #  qsub -cwd -l mem_free=3000M -v MYMODIS=aqua_lst1km20020706.LST_Night_1km.filt cea_launch_grassjob_55min.sh
     #
     # WATCH
     #  watch 'qstat  | grep "$USER\|job-ID"'
     #    Under the state column you can see the status of your job. Some of the codes are
     #    * r: the job is running
     #    * t: the job is being transferred to a cluster node
     #    * qw: the job is queued (and not running yet)
     #    * Eqw: an error occurred with the job
     #
     ###########

     # mount shared filesystem (not needed on al clusters)
     gfsmount
     # Change to the directory where the files are located
     export GFSDIR=/gfs/`whoami`
     cd $GFSDIR

     export MYGDATA=$GFSDIR/grassdata

     ########### nothing to change below ###########
     export MODISMAP="$MYMODIS"

     # use map name as MAPSET to avoid GRASS lock
     MYMAPSET=`echo $MYMODIS | sed 's+_1km.filt++g'`
     MYLOC=pat
     MYUSER=$MYMAPSET
     TARGETMAPSET=modisLSTinterpolation

     GRASS_BATCH_JOB=$HOME/modis_interpolation_GRASS_RST.sh

     ####

     # better say where to find libs and bins:
     export PATH=$HOME/binaries/bin:$PATH
     export LD_LIBRARY_PATH=$HOME/binaries/lib/

     rm -f modis_rst.$MYMODIS.out modis_rst.$MYMODIS.err

     # Set the global grassrc file with individual file name
     # don't use HOME but $GFSDIR:
     MYGISRC="$GFSDIR/.grassrc6.$MYUSER.`uname -n`.$MYMODIS"

     #generate GISRCRC
     echo "GISDBASE: $MYGDATA" > "$MYGISRC"
     echo "LOCATION_NAME: $MYLOC" >> "$MYGISRC"
     echo "MAPSET: $MYMAPSET" >> "$MYGISRC"
     echo "GRASS_GUI: text"   >> "$MYGISRC"

     echo "MYGISRC: $MYGISRC"
     cat $MYGISRC

     # say that we are running
     echo "GISDBASE=$MYGDATA/$MYLOC/$MYMAPSET" > $GFSDIR/running_job.$JOB_NAME$.$SGE_CELL.txt
     echo "SGE_JOBNAME: $JOB_NAME; SGE_CELL: $SGE_CELL" >> $GFSDIR/running_job.$JOB_NAME.$SGE_CELL.txt

     # path to GRASS settings file
     export GISRC=$MYGISRC

     # vars defined above:
     export GRASS_BATCH_JOB
     export MODISMAP

     # run the GRASS job:
     $HOME/binaries/bin/grass64 -c -text $MYGDATA/$MYLOC/$MYMAPSET

     # copy over result to target mapset
     export INMAP=${MYMODIS}_rst_model
     export INMAPSET=$MYMAPSET
     export OUTMAP=`echo $INMAP | sed 's+_1km.filt_rst_model+_1km.rst+g'`
     export GRASS_BATCH_JOB=$HOME/gcopyjob.sh
     $HOME/binaries/bin/grass64 -text $MYGDATA/$MYLOC/$TARGETMAPSET

     # remove tmp mapset
     rm -rf $MYGDATA/$MYLOC/$MYMAPSET
     rm -f $GFSDIR/running_job.$JOB_NAME$.$SGE_CELL.txt ${MYGISRC}

     echo "Hopefully successfully finished"

     # unmount shared filesystem (not needed on al clusters)
     cd /
     fusermount -u $GFSDIR

     exit 0

Launch many jobs through "for" loop as described in the PBS section above.