1. Introduction

On large-scale computers, many users must share available resources. Because of this, you cannot just log on to one of these systems, upload your programs, and start running them. Essentially, your programs (called batch jobs) have to "get in line" and wait their turn. And, there is more than one of these lines (called queues) from which to choose. Some queues have a higher priority than others (like the express checkout at the grocery store). The queues available to you are determined by the projects that you are involved with.

The jobs in the queues are managed and controlled by a batch queuing system, without which, users could overload systems, resulting in tremendous performance degradation. The queuing system will run your job as soon as it can while still honoring the following:

We use the PBS Professional queuing system. The PBS module should be loaded automatically for you at login, allowing you access to the PBS commands.

2. Anatomy of a Batch Script

A batch script is simply a small text file that can be created with a text editor such as vi or notepad. You may create your own from scratch, or start with one of the sample batch scripts available in $SAMPLES_HOME. Although the specifics of a batch script will differ slightly from system to system, a basic set of components are always required, and a few components are just always good ideas. The basic components of a batch script must appear in the following order:

IMPORTANT: Not all applications on Linux systems can read DOS-formatted text files. PBS does not handle ^M characters well, nor do some compilers. To avoid complications, please remember to convert all DOS-formatted ASCII text files with the dos2unix utility before use on any HPC system. Users are also cautioned against relying on ASCII transfer mode to strip these characters, as some file transfer tools do not perform this function.

2.1. Specify Your Shell

First of all, remember that your batch script is a script. It's a good idea to specify which shell your script is written in. Unless you specify otherwise, PBS will use your default login shell to run your script. To tell PBS which shell to use, start your script with a line similar to the following, where shell is either bash, sh, ksh, csh, or tcsh:

#!/bin/shell

2.2. Required PBS Directives

The next block of your script will tell PBS about the resources that your job needs by including PBS directives. These directives are actually a special form of comment, beginning with "#PBS". As you might suspect, the # character tells the shell to ignore the line, but PBS reads these directives and uses them to set various values. IMPORTANT!! All PBS directives MUST come before the first line of executable code in your script, otherwise they will be ignored.

Every script must include directives for the following:

PBS also provides additional optional directives. These are discussed in Optional PBS Directives, below.

2.2.1. Number of Cores per Node

Before PBS can schedule your job, it needs to know how many cores per node are required. This is accomplished with the "ncpus" directive. In general this value is always set to the total number of cores on the node (40) and is included on the same line as "select" and "mpiprocs" directives. It can, if desired, be specified on a separate line. There are situations where a user might want to specify a ncpus value less than the maximum number of cores; the most notable case being for a serial code. The ncpus value is also used by PBS to determine the amount of memory allowed for your job on that node; the formula is:

memory=ncpus/40 x total_node_memory

So for a serial or small MPI job utilizing half or less of the total cores on the node, the user must be careful to take into consideration the memory requirements of each executable before specifying an ncpus value less than 40. Also, in this case, a user may allow other small jobs to share the node. To allow this the PBS "place" directive should be set to "free". Below are several examples for specifying the number of cores per node.

Example 1: Serial code requiring 1/40 of the node's memory, and that will allow other jobs to run on its assigned node.

#PBS -l select=1:ncpus=1
#PBS -l place=free

Example 2: Serial code requiring 2/40 of the node's memory, and that will allow other jobs to run on its assigned node.

#PBS -l select=1
#PBS -l ncpus=2
#PBS -l place=free

Example 3: Serial or OpenMP code requiring all of the node's memory, and that will NOT allow other jobs to run on its assigned node.

#PBS -l select=1:ncpus=40
#PBS -l place=excl

2.2.2. Number of Nodes and Processes per Node

Before PBS can schedule your job, it needs to know how many nodes you want. Before your job can be run, it will also need to know how many processes you want to run on each of those nodes. In general, you would specify one process per core, but you might want more or fewer processes depending on the programming model you are using. See Example Scripts (below) for alternate use cases.

Both the number of nodes and processes per node are specified using the same directive as follows, where N1 is the number of nodes you are requesting and N2 is the number of processes per node:

#PBS -l select=N1:ncpus=40:mpiprocs=N2

To request Centennial GPU nodes:

#PBS -l select=N1:ncpus=40:mpiprocs=N2:ngpus=1

To request Centennial large-memory nodes:

#PBS -l select=N1:ncpus=40:mpiprocs=N2:bigmem=1

2.2.3. How Nodes Should Be Allocated

Some default behaviors in PBS have the potential to seriously impair the ability of your scripts to run in certain situations and could impose restrictions on submitted jobs that might cause them to wait much longer in the queue than necessary. To prevent these situations from occurring, the following PBS directive is required in all batch scripts on Centennial:

#PBS -l place=scatter:excl

This line indicates to PBS that the job has exclusive access to the requested nodes.

Also, jobs can share nodes with other jobs whose nodes are not fully utilized by adding the "pack=1" option, as follows:

#PBS -l select=N1:ncpus=40:mpiprocs=N2:pack=1

Use the above directive for sharing nodes.

For a further explanation of these directives, see the qsub man page.

2.2.4. How Long to Run

Next, PBS needs to know how long your job will run. For this, you will have to make an estimate. There are three things to keep in mind.

To specify how long your job will run, include the following directive:

#PBS -l walltime=HHH:MM:SS

2.2.5. Which Queue to Run In

Now, PBS needs to know which queue you want your job to run in. Your options here are determined by your project. Most users only have access to the debug, standard, interactive, and background queues. Other queues exist, but access to these queues is restricted to projects that have been granted special privileges due to urgency or importance, and they will not be discussed here. As their names suggest, the standard and debug queues should be used for normal day-to-day and debugging jobs. The background queue, however, is a bit special because although it has the lowest priority, jobs that run in this queue are not charged against your project allocation. Users may choose to run in the background queue for several reasons:

To see the list of queues available on the system, use the show_queues command. To specify the queue you want your job to run in, include the following directive:

#PBS -q queue_name

2.2.6. Your Project ID

PBS now needs to know which project ID to charge for your job. You can use the show_usage command to find the projects that are available to you and their associated project IDs. In the show_usage output, project IDs appear in the column labeled "Subproject." Note: Users with access to multiple projects should remember that the project they specify may limit their choice of queues.

To specify the Project ID for your job, include the following directive:

#PBS -A Project_ID

2.3. The Execution Block

Once the PBS directives have been supplied, the execution block may begin. This is the section of your script that contains the actual work to be done. A well written execution block will generally contain the following stages:

3. Submitting Your Job

Once your batch script is complete, you will need to submit it to PBS for execution using the qsub command. For example, if you have saved your script into a text file named run.pbs, you would type "qsub run.pbs".

Occasionally you may want to supply one or more directives directly on the qsub command line. Directives supplied in this way override the same directives if they are already included in your script. The syntax to supply directives on the command line is the same as within a script except that #PBS is not used. For example:

qsub -l walltime=HHH:MM:SS run.pbs

4. Simple Batch Script Example

The batch script below contains all of the required directives and common script components discussed above.

#!/bin/bash ##Specify your shell
## Required PBS Directives --------------------------------------
#PBS -A Project_ID
#PBS -q standard
#PBS -l select=8:ncpus=40:mpiprocs=40
#PBS -l place=scatter:excl
#PBS -l walltime=12:00:00
#PBS -j oe

## Execution Block ---------------------------------------------
# Environment Setup 
# cd to your scratch directory
cd ${WORKDIR}

# create a job-specific subdirectory based on JOBID and cd to it
JOBID=`echo ${PBS_JOBID} | cut -d '.' -f 1`
mkdir -p ${JOBID}
cd ${JOBID}

## Launching ----------------------------------------------------
# copy executable from $HOME and submit it
cp ${HOME}/mpicode.x .

# The following line provides an example of setting up and running
#  an SGI MPT parallel code built with the default compiler and default SGI MPT
#  MPI.
mpiexec_mpt -n 320 ./mpicode.x > out.dat

# The following three lines provide an example of setting up and running
#  an IntelMPI MPI  parallel code built with the default compiler.
module unload mpi/sgimpt/2.15 
module load mpi/intelmpi/2017.1.132
mpirun ./mpicode.x > out.dat

## Clean up  -----------------------------------------------------
# Remove temporary files
rm *.o *.temp

5. Job Management Commands

The table below contains commands for managing your jobs in PBS.

**Estimated start times are only available for a small number of jobs and are subject to frequent change as new jobs are queued.

6. Optional PBS Directives

In addition to the required directives mentioned above, PBS has many other directives, but most users will only use a few of them. Some of the more useful optional directives are listed below.

6.1. Job Identification Directives

Job identification directives allow you to identify characteristics of your jobs. These directives are voluntary, but strongly encouraged. The following table contains some useful job identification directives.

6.1.1. Application Name

The "-l application" directive allows you to identify the application being used by your job. This helps the program to accurately assess application usage and to ensure that adequate software licenses and appropriate software are purchased. To use this directive, add a line in the following form to your batch script:

#PBS -l application=application_name
Or to your qsub command
qsub -l application=application_name

A list of application names for use with this directive can be found in $SAMPLES_HOME/Application_Name/application_names on Centennial.

6.1.2. Job Name

The "-N" directive allows you to designate a name for your job. In addition to being easier to remember than a numeric job ID, the PBS environment variable, $PBS_JOBNAME, inherits this value and can be used instead of the job ID to create job-specific output directories. To use this directive, add a line in the following form to your batch script:

#PBS -N job_20
Or to your qsub command
qsub -N job_20...

6.2. Job Environment Directives

Job environment directives allow you to control the environment in which your script will operate. The following table contains a few useful job environment directives.

6.2.1. Interactive Batch Shell

The "-I" directive allows you to request an interactive batch shell. Within that shell, you can perform normal Unix commands, including launching parallel jobs. To use "-I", append it to the end of your qsub request. You may also use the "-X" option to allow for X-Forwarding to run X-Windows-based Graphical interfaces on the compute node. For example:

qsub -A Project_ID -q debug -l select=2:ncpus=40:mpiprocs=40 -l place=scatter:excl -l walltime=1:00:00 -X -I

6.2.2. Export All Variables

The "-V" directive tells PBS to export all of the environment variables from your login environment into your batch environment. To use this directive, add a line in the following form to your batch script:

#PBS -V
Or to your qsub command
qsub -V ...

6.2.3. Export Specific Variables

The "-v" directive tells PBS to export specific environment variables from your login environment into your batch environment. To use this directive, add a line in one of the following forms to your batch script:

#PBS -v DISPLAY
Or to your qsub command
qsub -v DISPLAY

Using either of these methods, multiple comma-separated variables can be included. It is also possible to set values for variables exported in this way, as follows:

qsub -v my_variable=my_value, ...

6.3. Reporting Directives

Reporting directives allow you to control what happens to standard output and standard error messages generated by your script. They also allow you to specify e-mail options to be executed at the beginning and end of your job.

6.3.1. Redirecting Stdout and Stderr

By default, messages written to stdout and stderr are captured for you in files named x.ojob_id and x.ejob_id, respectively, where x is either the name of the script or the name specified with the "-N" directive, and job_id is the ID of the job. If you want to change this behavior, the "-o" and "-e" directives allow you to redirect stdout and stderr messages to different named files. The "-j" directive allows you to combine stdout and stderr into the same file.

6.3.2. Setting up E-mail Alerts

Many users want to be notified when their jobs begin and end. The "-m" directive makes this possible. If you use this directive, you will also need to supply the "-M" directive with one or more e-mail addresses to be used.

For example:

#PBS -m be
#PBS -M joesmith@mail.mil,joe.smith@us.army.mil

6.4. Job Dependency Directives

Job dependency directives allow you to specify dependencies that your job may have on other jobs. This allows users to control the order jobs run in. These directives will generally take the following form:

#PBS -W depend=dependency_expression

where dependency_expression is a comma-delimited list of one or more dependencies, and each dependency is of the form:

type:jobids

where type is one of the directives listed below, and jobids is a colon-delimited list of one or more job IDs that your job is dependent upon.

For example, run a job after completion (success or failure) of job ID 1234:

#PBS -W depend=afterany:1234

Or, run a job after successful completion of job ID 1234:

#PBS -W depend=afterok:1234

For more information about job dependencies, see the qsub man page.

7. Environment Variables

7.1. PBS Environment Variables

While there are many PBS environment variables, you only need to know a few important ones to get started using PBS. The table below lists the most important PBS environment variables and how you might generally use them.

The following additional PBS variables may be useful to some users.

7.2. Other Important Environment Variables

In addition to the PBS environment variables, the table below lists a few other variables which are not specifically associated with PBS. These variables are not generally required, but may be important depending on your job.

8. Example Scripts

All of the script examples shown below contain a "Cleanup" section which demonstrates how to automatically archive your data using the transfer queue and clean up your $WORKDIR after your job completes. Using this method helps to avoid data loss, and ensures that your allocation is not charged for idle cores while performing file transfer operations.

8.1. MPI Script

The following script is for a 320-core MPI job running for 20 hours in the standard queue.

#!/bin/ksh
## Required Directives ------------------------------------
#PBS -l select=8:ncpus=40:mpiprocs=40
#PBS -l place=scatter:excl
#PBS -l walltime=20:00:00
#PBS -q standard
#PBS -A Project_ID

## Optional Directives ------------------------------------
#PBS -N testjob
#PBS -j oe
#PBS -M my_email@mail.mil
#PBS -m be

## Execution Block ----------------------------------------
# Environmental Setup
# the following environment variable is not required, but will
# optimally assign processes to cores and improve memory use.
export MPI_DSM_DISTRIBUTE=yes

. /usr/share/Modules/init/ksh

# cd to your scratch directory
cd ${WORKDIR}

# create a job-specific subdirectory based on JOBID and cd to it
JOBID=`echo ${PBS_JOBID} | cut -d '.' -f 1`
mkdir -p ${JOBID}
cd ${JOBID}

# copy data from $HOME
cp ${HOME}/my_data_dir/*.dat .

# copy the executable from $HOME
cp ${HOME}/my_prog.exe .

## Launching ----------------------------------------------

# for intelmpi, your launch command is as follows:
module unload mpi/sgimpt/2.15
module load module load mpi/intelmpi/2017.1.132
mpirun ./my_prog.exe > my_prog.out

# for SGI MPT MPI, your launch command is as follows:
mpiexec_mpt -n 320 ./my_prog.exe > my_prog.out

## Cleanup ------------------------------------------------
# archive your results
# Using the "here document" syntax, create a job script
# for archiving your data.
cd ${WORKDIR}
rm -f archive_job
cat >archive_job <<END
#!/bin/bash
#PBS -l walltime=12:00:00
#PBS -q transfer
#PBS -A Project_ID
#PBS -l select=1:ncpus=1
#PBS -j oe
#PBS -S /bin/bash
cd ${WORKDIR}

# tar local directory $JOBID into ${JOBID}.tar and put the tar file 
# in remote directory ${ARCHIVE_HOME}/myprogdir:

archive put -C  myprogdir -t ${JOBID}.tar $JOBID || echo "ERROR: Archive of ${JOBID}.tar to ${ARCHIVE_HOME}/myprogdir  failed...."

archive ls myprogdir/${JOBID}
# Remove scratch directory from the file system.
cd ${WORKDIR}
rm -rf ${JOBID}
END

# Submit the archive job script.
qsub archive_job

8.2. MPI Script (accessing more memory per process)

By default, an MPI job runs one process per core, with all processes sharing the available memory on the node. If you need more memory per process, then your job needs to run fewer MPI processes per node.

The following script requests 320 cores, but because mpiprocs is set to 1, it uses only one core (and one MPI process) per node for an MPI job running for 20 hours in the standard queue.

Note the use of the $BC_NODE_ALLOC environment variable (nodes allocated for this job). This would run 8 processes, each with access to 124 GB of memory.

#!/bin/ksh
## Required Directives ------------------------------------
#PBS -l select=8:ncpus=40:mpiprocs=1
#PBS -l place=scatter:excl
#PBS -l walltime=20:00:00
#PBS -q standard
#PBS -A Project_ID

## Optional Directives ------------------------------------
#PBS -N testjob
#PBS -j oe
#PBS -M my_email@mail.mil
#PBS -m be

## Execution Block ----------------------------------------
# Environmental Setup
# the following environment variable is not required, but will
# optimally assign processes to cores and improve memory use.
export MPI_DSM_DISTRIBUTE=yes

# cd to your scratch directory
cd ${WORKDIR}

# create a job-specific subdirectory based on JOBID and cd to it
JOBID=`echo ${PBS_JOBID} | cut -d '.' -f 1`
if [ ! -d ${JOBID} ]; then
  mkdir -p ${JOBID}
fi
cd ${JOBID}

# copy input from $HOME
cp ${HOME}/my_data_dir/*.dat .

# copy the executable from $HOME
cp ${HOME}/my_prog.exe .

## Launching ----------------------------------------------
# for intelmpi, your launch command is as follows:
module unload mpi/sgimpt/2.15
module load module load mpi/intelmpi/2017.1.132
mpirun ./my_prog.exe > my_prog.out

# for SGI MPT MPI, your launch command is as follows:
mpiexec_mpt -n 8 ./my_prog.exe > my_prog.out

## Cleanup ------------------------------------------------
# archive your results
# Using the "here document" syntax, create a job script
# for archiving your data.
cd ${WORKDIR}
rm -f archive_job
cat >archive_job <<END
#!/bin/bash
#PBS -l walltime=12:00:00
#PBS -q transfer
#PBS -A Project_ID
#PBS -l select=1:ncpus=1
#PBS -j oe
#PBS -S /bin/bash
cd ${WORKDIR}

# tar local directory $JOBID into ${JOBID}.tar and put the tar file 
# in remote directory ${ARCHIVE_HOME}/myprogdir:

archive put -C  myprogdir -t ${JOBID}.tar $JOBID || echo "ERROR: Archive of ${JOBID}.tar to ${ARCHIVE_HOME}/myprogdir  failed...."
archive ls myprogdir/${JOBID}
# Remove scratch directory from the file system.
cd ${WORKDIR}
rm -rf ${JOBID}
END

# Submit the archive job script.
qsub archive_job

8.3. OpenMP Script

The following script is for an OpenMP job using one thread per core on a single node and running for 20 hours in the standard queue. Note the use of the $BC_CORES_PER_NODE environment variable.

#!/bin/ksh
## Required Directives ------------------------------------
#PBS -l select=1:ncpus=40:mpiprocs=40
#PBS -l place=scatter:excl
#PBS -l walltime=20:00:00
#PBS -q standard
#PBS -A Project_ID

## Optional Directives ------------------------------------
#PBS -N testjob
#PBS -j oe
#PBS -M my_email@mail.mil
#PBS -m be

## Execution Block ----------------------------------------
# Environmental Setup
# cd to your scratch directory
cd ${WORKDIR}

# create a job-specific subdirectory based on JOBID and cd to it
JOBID=`echo ${PBS_JOBID} | cut -f1 -d'.'`
if [ ! -d ${JOBID} ]; then
  mkdir -p ${JOBID}
fi
cd ${JOBID}

# copy data files from $HOME
cp ${HOME}/my_data_dir/*.dat .

# copy the executable from $HOME
cp ${HOME}/my_prog.exe .

## Launching ----------------------------------------------
export OMP_NUM_THREADS=${BC_CORES_PER_NODE}
./my_prog.exe > my_prog.out

## Cleanup ------------------------------------------------
# archive your results
# Using the "here document" syntax, create a job script
# for archiving your data.
cd ${WORKDIR}
rm -f archive_job
cat >archive_job <<END
#!/bin/bash
#PBS -l walltime=12:00:00
#PBS -q transfer
#PBS -A Project_ID
#PBS -l select=1:ncpus=1
#PBS -j oe
#PBS -S /bin/bash
cd ${WORKDIR}

# tar local directory $JOBID into ${JOBID}.tar and put the tar file 
# in remote directory ${ARCHIVE_HOME}/myprogdir:

archive put -C  myprogdir -t ${JOBID}.tar $JOBID || echo "ERROR: Archive of ${JOBID}.tar to ${ARCHIVE_HOME}/myprogdir  failed...."
archive ls myprogdir/${JOBID}

# Remove scratch directory from the file system.
cd ${WORKDIR}
rm -rf ${JOBID}
END

# Submit the archive job script.
qsub archive_job

8.4. Hybrid MPI/OpenMP Script

The following script uses 320 cores with one MPI task per node and one thread per core. Note the use of the $BC_CORES_PER_NODE and $BC_NODE_ALLOC environment variables.

#!/bin/ksh
## Required Directives ------------------------------------
#PBS -l select=8:ncpus=40:mpiprocs=1
#PBS -l place=scatter:excl
#PBS -l walltime=20:00:00
#PBS -q standard
#PBS -A Project_ID

## Optional Directives ------------------------------------
#PBS -N testjob
#PBS -j oe
#PBS -M my_email@mail.mil
#PBS -m be

## Execution Block ----------------------------------------
# Environmental Setup
# the following environment variable is not required, but will
# optimally assign processes to cores and improve memory use.
export MPI_DSM_DISTRIBUTE=yes

# cd to your scratch directory
cd ${WORKDIR}

# create a job-specific subdirectory based on JOBID and cd to it
JOBID=`echo ${PBS_JOBID} | cut -d '.' -f 1`
if [ ! -d ${JOBID} ]; then
  mkdir -p ${JOBID}
fi
cd ${JOBID}

# copy input data from $HOME
cp ${HOME}/my_data_dir/*.dat .

# copy the executable from $HOME
cp ${HOME}/my_prog.exe .

## Launching ----------------------------------------------
export OMP_NUM_THREADS=${BC_CORES_PER_NODE}
# for intelmpi, your launch command is as follows:
module unload mpi/sgimpt/2.15
module load module load mpi/intelmpi/2017.1.132
mpirun ./my_prog.exe > my_prog.out

# for SGI MPT MPI, your launch command is as follows:
mpiexec_mpt -n 8 ./my_prog.exe > my_prog.out

## Cleanup ------------------------------------------------
# archive your results
# Using the "here document" syntax, create a job script
# for archiving your data.
cd ${WORKDIR}
rm -f archive_job
cat >archive_job <<END
#!/bin/bash
#PBS -l walltime=12:00:00
#PBS -q transfer
#PBS -A Project_ID
#PBS -l select=1:ncpus=1
#PBS -j oe
#PBS -S /bin/bash
cd ${WORKDIR}

# tar local directory $JOBID into ${JOBID}.tar and put the tar file 
# in remote directory ${ARCHIVE_HOME}/myprogdir:

archive put -C  myprogdir -t ${JOBID}.tar $JOBID || echo "ERROR: Archive of ${JOBID}.tar to ${ARCHIVE_HOME}/myprogdir  failed...."
archive ls myprogdir/${JOBID}

# Remove scratch directory from the file system.
cd ${WORKDIR}
rm -rf ${JOBID}
END

# Submit the archive job script.
qsub archive_job

8.5. Hybrid MPI/OpenMP Script (Alternative Example)

The following script uses 640 cores with two MPI tasks per node and one thread per core. Note the use of the $BC_CORES_PER_NODE and $BC_NODE_ALLOC environment variables.

#!/bin/ksh
## Required Directives ------------------------------------
#PBS -l select=16:ncpus=40:mpiprocs=2
#PBS -l place=scatter:excl
#PBS -l walltime=20:00:00
#PBS -q standard
#PBS -A Project_ID

## Optional Directives ------------------------------------
#PBS -N testjob
#PBS -j oe
#PBS -M my_email@mail.mil
#PBS -m be

## Execution Block ----------------------------------------
# Environmental Setup
# the following environment variable is not required, but will
# optimally assign processes to cores and improve memory use.
export MPI_DSM_DISTRIBUTE=yes

# cd to your scratch directory
cd ${WORKDIR}

# create a job-specific subdirectory based on JOBID and cd to it
JOBID=`echo ${PBS_JOBID} | cut -d '.' -f 1`
if [ ! -d ${JOBID} ]; then
  mkdir -p ${JOBID}
fi
cd ${JOBID}

# copy input data from $HOME
cp ${HOME}/my_data_dir/*.dat .

# copy the executable from $HOME
cp ${HOME}/my_prog.exe .

## Launching ----------------------------------------------
export OMP_NUM_THREADS=${BC_CORES_PER_NODE}
# for intelmpi, your launch command is as follows:
module unload mpi/sgimpt/2.15
module load module load mpi/intelmpi/2017.1.132
mpirun ./my_prog.exe > my_prog.out

# for SGI MPT MPI, your launch command is as follows:
mpiexec_mpt -n 32 ./my_prog.exe > my_prog.out

## Cleanup ------------------------------------------------
# archive your results
# Using the "here document" syntax, create a job script
# for archiving your data.
cd ${WORKDIR}
rm -f archive_job
cat >archive_job <<END
#!/bin/bash
#PBS -l walltime=12:00:00
#PBS -q transfer
#PBS -A Project_ID
#PBS -l select=1:ncpus=1
#PBS -j oe
#PBS -S /bin/bash
cd ${WORKDIR}

# tar local directory $JOBID into ${JOBID}.tar and put the tar file 
# in remote directory ${ARCHIVE_HOME}/myprogdir:

archive put -C  myprogdir -t ${JOBID}.tar $JOBID || echo "ERROR: Archive of ${JOBID}.tar to ${ARCHIVE_HOME}/myprogdir  failed...."
archive ls myprogdir/${JOBID}

# Remove scratch directory from the file system.
cd ${WORKDIR}
rm -rf ${JOBID}
END

# Submit the archive job script.
qsub archive_job