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neuroscience/fedora/musings

Tue 31 May 2016

Some tips and tricks for running simulations on a cluster

Posted by ankur in Research (1056 words, approximately a 5 minute read)

To begin with, you must use a terminal multiplexer! I use Byobu with tmux to multiplex a single SSH session. I use it on all my machines. It's an excellent tool.

Monitoring your jobs

Three of my Byobu screens run these commands to monitor the queue and my jobs:

watch -n 30 qstat main
watch -n 30 qstat -B
watch -n 30 /usr/local/maui/bin/showq -u asinha

showq may be installed elsewhere. Use which showq to locate it. More information on the commands can be found in their manuals:

man watch
man qstat

Remember, to find a man page, you can use the apropos command.

I run all my simulations in a specific directory on the shared data disk. I usually also monitor this folder. It gives me an idea of how much my simulations have progressed. Something like this works:

watch -n 30 'du -sch *' # in the directory that stores simulation results*

Use Git

Of course. If you make frequent changes, you must use a version control system. I stick to git myself. You can use svn or hg if you wish - whatever floats your boat.

An issue I've stumbled upon while working with the cluster is that the program you want it to run is not loaded into memory until your job begins to run. So, if you want to run a certain version of your program on the cluster, say some version_1, you must not make any changes to this version until the queued job has begun to run. This is extremely inconvenient, especially if you make frequent changes to your simulations, as is often the case in research. I would, for example, like to queue separate jobs in parallel for a myriad of tiny changes and then compare results.

Enter git work-tree! The simplest solution to the aforementioned issue is to checkout different work-trees for commits you want to test and queue up jobs for each individually. This would work really well. Once the simulation finishes, you can remove the work-tree.

Unfortunately, clusters usually run stable long term support oriented versions of Linux distributions - EL/CentOS/Scientific. As a result, it's quite probable that the version of git on the cluster doesn't support work-trees - as is the case with the cluster I use. I came up with a workaround which works somewhat like work-trees - I manually clone my source repository to a temporary location, checkout the commit I want to run (which is what work-trees sort of are), and set up a job that runs this particular simulation version. It uses two scripts:

  • A template PBS script for the simulation run. This will be passed to qsub.
  • A script that clones my repo, checks out the required commit, completes the template script, and calls qsub to queue up the job.

The first is a simple PBS script:

# File: run-sim.sh

#PBS -l walltime=48:00:00
#PBS -l nodes=50
#PBS -m abe
#PBS -N nest_v_s

module unload mpi/mpich-x86_64
module load mvapich2-1.7

SIM_PATH="/stri-data/asinha/simulations-nest/"
SIM_TIME=""
PROGRAM_PATH="$SIM_PATH""$SIM_TIME""/Sinha2016/src/Sinha2016.py"
RESULT_PATH="$SIM_PATH""$SIM_TIME""/result/"
NUM_NODES=50

echo ------------------------------------------------------
echo 'Job is running on nodes'; cat $PBS_NODEFILE
echo ------------------------------------------------------
echo PBS: qsub is running on $PBS_O_HOST
echo PBS: originating queue is $PBS_O_QUEUE
echo PBS: executing queue is $PBS_QUEUE
echo PBS: working directory is $PBS_O_WORKDIR
echo PBS: execution mode is $PBS_ENVIRONMENT
echo PBS: job identifier is $PBS_JOBID
echo PBS: job name is $PBS_JOBNAME
echo PBS: node file is $PBS_NODEFILE
echo PBS: current home directory is $PBS_O_HOME
echo PBS: PATH = $PBS_O_PATH
echo ------------------------------------------------------

echo "ANKUR>> Begun at $SIM_TIME"
echo "ANKUR>> Script: ${0}"

mkdir -pv $RESULT_PATH
cd $RESULT_PATH

/usr/local/bin/mpiexec -n $NUM_NODES python $PROGRAM_PATH

END_TIME=$(date +%Y%m%d%H%M)
echo "ANKUR>> Ended at $END_TIME"

It sets up the required PBS options, then loads the MPI module I wish to use. It creates a directory where my simulation's results will be stored, enters it, and then uses mpiexec to run my Python program.

The second script is a wrapper that clones the required commit, sets up the correct paths in the above script and the calls qsub:

# File: setup-job.sh

SOURCE_PATH="/home/asinha/Documents/02_Code/00_repos/00_mine/Sinha2016/"
GIT_COMMIT=""
SIM_PATH="/stri-data/asinha/simulations-nest/"
SIM_TIME=$(date +%Y%m%d%H%M)
RUN_SCRIPT="scripts/cluster/nest-runsim.sh"
RUN_NEW=""
ERROR="no"
NUM_NODES=50
CUR_SIM_PATH=""

function queue_task
{
    pushd "$CUR_SIM_PATH"
        qsub "$RUN_NEW"
    popd
}

function setup_env
{
    CUR_SIM_PATH="$SIM_PATH""$SIM_TIME"
    echo "This simulation will run in: $CUR_SIM_PATH"
    mkdir -pv "$CUR_SIM_PATH"

    pushd "$CUR_SIM_PATH"
        echo "Cloning source repository..."
        git clone "$SOURCE_PATH" "Sinha2016"

        pushd "Sinha2016"
            echo "Checking out commit $GIT_COMMIT..."
            git checkout -b this_sim "$GIT_COMMIT"
            if [ "$?" -ne 0 ]
            then
                echo "Error occured. Could not checkout $GIT_COMMIT. Exiting..."
                ERROR="yes"
            fi
        popd

        if [ "xyes" ==  x"$ERROR" ]
        then
            exit -1
        fi

        RUN_NEW="nest_""$GIT_COMMIT"".sh"
        echo "Setting up $RUN_NEW..."
        cp "$SOURCE_PATH""$RUN_SCRIPT" "$RUN_NEW" -v
        sed -i "s|nest_v_s|nest_$GIT_COMMIT|" "$RUN_NEW"
        sed -i "s|nodes=.*|nodes=$NUM_NODES|" "$RUN_NEW"
        sed -i "s|NUM_NODES=.*|NUM_NODES=$NUM_NODES|" "$RUN_NEW"
        sed -i "s|SIM_TIME=.*|SIM_TIME=$SIM_TIME|" "$RUN_NEW"
    popd
}

function usage
{
    echo "Usage: $0"
    echo "Queue up a job to run a particular git commit"
    echo "$0 <git_commit> <number_nodes>"
}

if [ "$#" -ne 2 ];
then
    echo "Error occurred. Exiting..."
    echo "Received $# arguments. Expected: 3"
    usage
    exit -1
fi

GIT_COMMIT="$1"
NUM_NODES="$2"
setup_env
queue_task

exit 0

This takes two arguments, as the usage function will tell you. The first argument is the commit you want to run the simulation for, and the second is the number of nodes you want to use. It'll clone your repository to a temporary location and checkout this specified commit. Then, it'll modify the first script run-sim.sh to set up the correct path to the code and also correctly specify the number of nodes you'd want to request. Finally, once all this is done, it'll call qsub run-sim.sh to queue up your job. I use unique date stamps as directory names to distinguish between simulation runs, but you can use another unique identifier.

Now, this copy of your code, at the specified commit will be used for the job you've queued. You can merrily go about tinkering with the main source repo without affecting queued up jobs. Yay!

Even though I've used Python here, you can use similar scripts for compiled languages. You'll simply have to compile your executable after you checkout the required commit.

Other miscellaneous stuff

My lab mate, Alex, recently introduced me to Anaconda. It's a great tool for that lets you install packages in your user specific directory. It contains quite a few python and other related packages. No need to use sudo with it, and you can use pip etc. with it too. It even lets you set up virtual environments and things.

I think that's it for today. I'll update the post with other things I find/learn as I continue my adventures with the cluster.


 
    
 
 

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