Submitting parallel OpenMPI jobs

SGE Configuration Intent

• Environments - used to categorize job/application type [serial or parallel]
• Queues - used to categorize job/application type [test (<1hr), short, long]
• Host Groups - used to categorize ownership, access, and priority
• User Groups - applied to host groups

Parallel Example

Using OpenMPI:

#!/bin/csh
#$ -pe mpi-8 32
#$ -q *@@nehalem (<- specifies any queue that can run on the nehalem host group)
module load ompi/1.3.2-intel
mpirun  -np $NSLOTS yourapplication

-pe mpi-8

-pe mpi-*

-pe mpi-* 24

-pe mpi-* 32

OpenMP Parallel Jobs

Using the -pe smp directive as detailed above is equivalent to asking permission to use multiple cores in your batch job. To run a job on multiple cores, you will also need to specify the number of cores by some method for the application. Some common methods of doing this are outlined below:

• MPI programs use the -np option to the mpirun command to specify the number of CPUs to run on. The mpi programs are part of the mpt module.
• openMP programs use the OMP_NUM_THREADS environment variable to control the number of CPUs the program runs on.
• Other programs may have specific flags or methods of starting parallel execution (for instance the %NProc= ``link 0 command in Gaussian 98).

Monitoring Batch Jobs

Jobs can be monitored using the qstat command. Some useful forms:

qstat without arguments will print the status of all jobs in the queue. The output shows the following:

* The job ID number
* Priority of job
* Name of job
* ID of user who submitted job
* State of the job: States can be
** t(ransferring)
** r(unning)
* Submit or start time and date of the job
* If running - the queue in which the job is running
* The function of the running job (MASTER or SLAVE)
* The job array task ID

qstat -f Job ID Provides a full listing of the job that has the listed Job ID (or all jobs if no Job ID is given). The output shows the following: For each queue the information printed consists of:

* the queue name
* the queue type: Types or a combination of types can be
** B(atch)
** P(arallel)
* The number of used and available job slots
* The load average on the queue host
* The architecture of the queue host
* The state of the queue - Queue states or a combination of states can be
** a(larm)
** A(larm)
** s(uspended)
** d(isable)
** D(isable)
** E(rror)

qstat -j [job_list] Prints either for all pending jobs or the jobs contained in job_list the reason for not being scheduled. Additional information can be obtained my looking at the man page for qstat. Type "man qstat" for additional information.

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Sun Grid Engine Quick-Start¶

The following sections give an overview of how to submit jobs, monitor job and host status, and how to use the SGE parallel environment.

Submitting Jobs¶

A job in SGE represents a task to be performed on a node in the cluster and contains the command line used to start the task. A job may have specific resource requirements but in general should be agnostic to which node in the cluster it runs on as long as its resource requirements are met.

Note

All jobs require at least one available slot on a node in the cluster to run.

Submitting jobs is done using the qsub command. Let's try submitting a simple job that runs the hostname command on a given cluster node:

sgeadmin@master:~$ qsub -V -b y -cwd hostname
Your job 1 ("hostname") has been submitted

• The -V option to qsub states that the job should have the same environment variables as the shell executing qsub (recommended)
• The -b option to qsub states that the command being executed could be a single binary executable or a bash script. In this case the command hostname is a single binary. This option takes a y or n argument indicating either yes the command is a binary or no it is not a binary.
• The -cwd option to qsub tells Sun Grid Engine that the job should be executed in the same directory that qsub was called.
• The last argument to qsub is the command to be executed (hostname in this case)

Notice that the qsub command, when successful, will print the job number to stdout. You can use the job number to monitor the job's status and progress within the queue as we'll see in the next section.

Monitoring Jobs in the Queue¶

Now that our job has been submitted, let's take a look at the job's status in the queue using the command qstat:

sgeadmin@master:~$ qstat
job-ID prior name user state submit/start at queue slots ja-task-ID
-------------------------------------------------------------------
1 0.00000 hostname sgeadmin qw 09/09/2009 14:58:00 1
sgeadmin@master:~$

From this output, we can see that the job is in the qw state which stands for queued and waiting. After a few seconds, the job will transition into a r, or running, state at which point the job will begin executing:

sgeadmin@master:~$ qstat
job-ID  prior   name       user         state submit/start at     queue  slots ja-task-ID
-----------------------------------------------------------------------------------------
1 0.00000 hostname   sgeadmin     r     09/09/2009 14:58:14                1
sgeadmin@master:~$

Once the job has finished, the job will be removed from the queue and will no longer appear in the output of qstat:

sgeadmin@master:~$ qstat
sgeadmin@master:~$

Now that the job has finished let's move on to the next section to see how we view a job's output.

Viewing a Job's Output¶

Sun Grid Engine creates stdout and stderr files in the job's working directory for each job executed. If any additional files are created during a job's execution, they will also be located in the job's working directory unless explicitly saved elsewhere.

The job's stdout and stderr files are named after the job with the extension ending in the job's number.

For the simple job submitted above we have:

sgeadmin@master:~$ ls hostname.*
hostname.e1 hostname.o1
sgeadmin@master:~$ cat hostname.o1
node001
sgeadmin@master:~$ cat hostname.e1
sgeadmin@master:~$

Notice that Sun Grid Engine automatically named the job hostname and created two output files: hostname.e1 and hostname.o1. The e stands for stderr and the o for stdout. The 1 at the end of the files' extension is the job number. So if the job had been named my_new_job and was job #23 submitted, the output files would look like:

my_new_job.e23 my_new_job.o23

Monitoring Cluster Usage¶

After a while you may be curious to view the load on Sun Grid Engine. To do this, we use the qhost command:

sgeadmin@master:~$ qhost
HOSTNAME ARCH NCPU LOAD MEMTOT MEMUSE SWAPTO SWAPUS
-------------------------------------------------------------------------------
global - - - - - - -
master lx24-x86 1 0.00 1.7G 62.7M 896.0M 0.0
node001 lx24-x86 1 0.00 1.7G 47.8M 896.0M 0.0

The output shows the architecture (ARCH), number of cpus (NCPU), the current load (LOAD), total memory (MEMTOT), and currently used memory (MEMUSE) and swap space (SWAPTO) for each node.

You can also view the average load (load_avg) per node using the '-f' option to qstat:

sgeadmin@master:~$ qstat -f
queuename qtype resv/used/tot. load_avg arch states
---------------------------------------------------------------------------------
[email protected] BIP 0/0/1 0.00 lx24-x86
---------------------------------------------------------------------------------
[email protected] BIP 0/0/1 0.00 lx24-x86

Creating a Job Script¶

In the 'Submitting a Job' section we submitted a single command hostname. This is useful for simple jobs but for more complex jobs where we need to incorporate some logic we can use a so-called job script. A job script is essentially a bash script that contains some logic and executes any number of external programs/scripts:

#!/bin/bash
echo "hello from job script!"
echo "the date is" `date`
echo "here's /etc/hosts contents:"
cat /etc/hosts
echo "finishing job :D"

As you can see, this script simply executes a few commands (such as echo, date, cat, etc.) and exits. Anything printed to the screen will be put in the job's stdout file by Sun Grid Engine.

Since this is just a bash script, you can put any form of logic necessary in the job script (i.e. if statements, while loops, for loops, etc.) and you may call any number of external programs needed to complete the job.

Let's see how you run this new job script. Save the script above to /home/sgeadmin/jobscript.sh on your StarCluster and execute the following as the sgeadmin user:

sgeadmin@master:~$ qsub -V jobscript.sh
Your job 6 ("jobscript.sh") has been submitted

Now that the job has been submitted, let's call qstat periodically until the job has finished since this job should only take a second to run once it's executed:

sgeadmin@master:~$ qstat
job-ID prior name user state submit/start at queue slots ja-task-ID
-------------------------------------------------------------------
6 0.00000 jobscript. sgeadmin qw 09/09/2009 16:18:43 1

sgeadmin@master:~$ qstat
job-ID prior name user state submit/start at queue slots ja-task-ID
-------------------------------------------------------------------
6 0.00000 jobscript. sgeadmin qw 09/09/2009 16:18:43 1

sgeadmin@master:~$ qstat
job-ID prior name user state submit/start at queue slots ja-task-ID
-------------------------------------------------------------------
6 0.00000 jobscript. sgeadmin qw 09/09/2009 16:18:43 1

sgeadmin@master:~$ qstat
job-ID prior name user state submit/start at queue slots ja-task-ID
-------------------------------------------------------------------
6 0.00000 jobscript. sgeadmin qw 09/09/2009 16:18:43 1

sgeadmin@master:~$ qstat
job-ID prior name user state submit/start at queue slots ja-task-ID
-------------------------------------------------------------------
6 0.55500 jobscript. sgeadmin r 09/09/2009 16:18:57 [email protected] 1

sgeadmin@master:~$ qstat
sgeadmin@master:~$

Now that the job is finished, let's take a look at the output files:

sgeadmin@master:~$ ls jobscript.sh*
jobscript.sh jobscript.sh.e6 jobscript.sh.o6
sgeadmin@master:~$ cat jobscript.sh.o6
hello from job script!
the date is Wed Sep 9 16:18:57 UTC 2009
here's /etc/hosts contents:
# Do not remove the following line or programs that require network functionality will fail
127.0.0.1 localhost.localdomain localhost
10.252.167.143 master
10.252.165.173 node001
finishing job :D
sgeadmin@master:~$ cat jobscript.sh.e6
sgeadmin@master:~$

We see from looking at the output that the stdout file contains the output of the echo, date, and cat statements in the job script and that the stderr file is blank meaning there were no errors during the job's execution. Had something failed, such as a command not found error for example, these errors would have appeared in the stderr file.

Deleting a Job from the Queue¶

What if a job is stuck in the queue, is taking too long to run, or was simply started with incorrect parameters? You can delete a job from the queue using the qdel command in Sun Grid Engine. Below we launch a simple 'sleep' job that sleeps for 10 seconds so that we can kill it using qdel:

sgeadmin@master:~$ qsub -b y -cwd sleep 10
Your job 3 ("sleep") has been submitted
sgeadmin@master:~$ qdel 3
sgeadmin has registered the job 3 for deletion

After running qdel you'll notice the job is gone from the queue:

sgeadmin@master:~$ qstat
sgeadmin@master:~$

OpenMPI and Sun Grid Engine¶

Note

• OpenMPI must be compiled with SGE support (–with-sge) to make use of the tight-integration between OpenMPI and SGE as documented in this section. This is the case on all of StarCluster's public AMIs.

• OpenMPI supports tight integration with Sun Grid Engine. This integration allows Sun Grid Engine to handle assigning hosts to parallel jobs and to properly account for parallel jobs.

OpenMPI Parallel Environment¶

StarCluster by default sets up a parallel environment, called "orte", that has been configured for OpenMPI integration within SGE and has a number of slots equal to the total number of processors in the cluster. You can inspect the SGE parallel environment by running:

sgeadmin@ip-10-194-13-219:~$ qconf -sp orte
pe_name            orte
slots              16
user_lists         NONE
xuser_lists        NONE
start_proc_args    /bin/true
stop_proc_args     /bin/true
allocation_rule    $fill_up
control_slaves     TRUE
job_is_first_task  FALSE
urgency_slots      min
accounting_summary FALSE

This is the default configuration for a two-node, c1.xlarge cluster (16 virtual cores).

Parallel Environment Allocation Rule

Notice the allocation_rule setting in the output of the qconf command in the previous section. This rule defines how to assign slots to a job. By default StarCluster uses the fill_up allocation rule. This rule causes SGE to greedily take all available slots on as many cluster nodes as needed to fulfill the slot requirements of a given job. For example, if a user requests 8 slots and a single node has 8 slots available, that job will run entirely on one node. If 5 slots are available on one node and 3 on another, it will take all 5 on that node, and all 3 on the other node.

The allocation rule can also be configured to distribute the slots around the cluster as evenly as possible by using the round_robin allocation_rule. For example, if a job requests 8 slots, it will go to the first node, grab a slot if available, move to the next node and grab a single slot if available, and so on wrapping around the cluster nodes again if necessary to allocate 8 slots to the job.

Finally, setting the allocation_rule to an integer number will cause the parallel environment to take a fixed number of slots from each host when allocating the job by specifying an integer for the allocation_rule. For example, if the allocation_rule is set to 1 then all slots have to reside on different hosts. If the special value $pe_slots is used then all slots for the parallel job must be allocated entirely on a single host in the cluster.

You can change the allocation rule for the orte parallel environment at any time using:

$ qconf -mp orte

This will open up vi (or any editor defined in the EDITOR environment variable) and let you edit the parallel environment settings. To change from fill_up to round_robin in the above example, change the allocation_rule line from:

allocation_rule    $fill_up

to:

allocation_rule    $round_robin

You can also change the rule to the pe_slots mode:

allocation_rule    $pe_slots

or specify a fixed number of slots per host to assign when allocating the job:

allocation_rule    1

After making the change and saving the file you can verify your settings using:

sgeadmin@ip-10-194-13-219:~$ qconf -sp orte
pe_name            orte
slots              16
user_lists         NONE
xuser_lists        NONE
start_proc_args    /bin/true
stop_proc_args     /bin/true
allocation_rule    $round_robin
control_slaves     TRUE
job_is_first_task  FALSE
urgency_slots      min
accounting_summary FALSE

Submitting OpenMPI Jobs using a Parallel Environment

The general workflow for running MPI code is:

1. Compile the code using mpicc, mpicxx, mpif77, mpif90, etc.
2. Copy the resulting executable to the same path on all nodes or to an NFS-shared location on the master node

Note

It is important that the path to the executable is identical on all nodes for mpirun to correctly launch your parallel code. The easiest approach is to copy the executable somewhere under /home on the master node since /home is NFS-shared across all nodes in the cluster.

3. Run the code on X number of machines using:

   $ mpirun -np X -hostfile myhostfile ./mpi-executable arg1 arg2 [...]
   

where the hostfile looks something like:

$ cat /path/to/hostfile
master  slots=2
node001 slots=2
node002 slots=2
node003 slots=2

However, when using an SGE parallel environment with OpenMPI you no longer have to specify the -np, -hostfile, -host, etc. options to mpirun. This is because SGE will automatically assign hosts and processors to be used by OpenMPI for your job. You also do not need to pass the –byslot and –bynode options to mpirun given that these mechanisms are now handled by the fill_up and round_robin modes specified in the SGE parallel environment.

Instead of using the above formulation create a simple job script that contains a very simplified mpirun call:

$ cat myjobscript.sh
mpirun /path/to/mpi-executable arg1 arg2 [...]

Then submit the job using the qsub command and the orte parallel environment automatically configured for you by StarCluster:

$ qsub -pe orte 24 ./myjobscript.sh

The -pe option species which parallel environment to use and how many slots to request. The above example requests 24 slots (or processors) using the orte parallel environment. The parallel environment automatically takes care of distributing the MPI job amongst the SGE nodes using the allocation_rule defined in the environment's settings.

You can also do this without a job script like so:

$ cd /path/to/executable
$ qsub -b y -cwd -pe orte 24 mpirun ./mpi-executable arg1 arg2 [...]

Etc

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Last modified: March, 12, 2019