The Sun Grid Engine queuing system is useful when you have a lot of tasks to execute and want to distribute the tasks over a cluster of machines. For example, you might need to run hundreds of simulations/experiments with varying parameters or need to convert 300 videos from one format to another. Using a queuing system in these situations has the following advantages:
Note
The SGE plugin is enabled by default for all clusters created by StarCluster - no additional configuration is required. The next section is for users that wish to customize the SGE install beyond the defaults.
The SGE plugin has advanced options that some users may wish to tune for their needs. In order to use these advanced options you must first define the SGE plugin in your config:
[plugin sge]
setup_class = starcluster.plugins.sge.SGEPlugin
Once the plugin has been defined the next step is to add the plugin to the plugins list in one of your cluster templates:
[cluster smallcluster]
plugins = sge
The final step is to set disable_queue=True in your cluster template. This tells StarCluster not to run the SGE plugin internally by default. This is needed given that we’re configuring the plugin manually ourselves:
Warning
It is important to set disable_queue=True when manually configuring the SGE plugin. If you dont the SGE plugin will run twice because the SGE plugin is currently a default in StarCluster.
[cluster smallcluster]
disable_queue = True
plugins = sge
By default StarCluster configures the master node as an execution host which means that the master node can accept and run jobs. In some cases you may not wish to run jobs on the master due to resource constraints. For example, if you’re generating a lot of NFS traffic in your jobs you may wish to completely dedicate the master to serving NFS rather than both running jobs and serving NFS.
To disable the master node being used as an execution host set master_is_exec_host=False in your sge plugin config:
[plugin sge]
setup_class = starcluster.plugins.sge.SGEPlugin
master_is_exec_host = False
Now whenever a new cluster is created with the SGE plugin enabled the master will not be configured as an execution host.
Of course, just because a queuing system is installed doesn’t mean you have to use it at all. You can run your tasks across the cluster in any way you see fit and the queuing system should not interfere. However, if you do not want or need SGE on your cluster simply set disable_queue=True in one of your cluster templates:
[cluster smallcluster]
disable_queue = True
This will skip the SGE install phase when creating a new cluster using the smallcluster template.
The following sections give an overview of how to submit jobs, monitor job and host status, and how to use the SGE parallel environment.
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
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.
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.
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
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
---------------------------------------------------------------------------------
all.q@master.c BIP 0/0/1 0.00 lx24-x86
---------------------------------------------------------------------------------
all.q@node001.c BIP 0/0/1 0.00 lx24-x86
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 all.q@node001.c 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.
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:~$
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.
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 $round_robin
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).
Notice the allocation_rule setting in the output of the qconf command in the previous section. This defines how to assign slots to a job. By default StarCluster configures round_robin allocation. This means that if a job requests 8 slots for example, it will go to the first machine, grab a single slot if available, move to the next machine and grab a single slot if available, and so on wrapping around the cluster again if necessary to allocate 8 slots to the job.
You can also configure the parallel environment to try and localize slots as much as possible using the fill_up allocation rule. With this rule, if a user requests 8 slots and a single machine has 8 slots available, that job will run entirely on one machine. If 5 slots are available on one host and 3 on another, it will take all 5 on that host, and all 3 on the other host. In other words, this rule will greedily take all slots on a given node until the slot requirement for the job is met.
You can switch between round_robin and fill_up modes using the following command:
$ qconf -mp orte
This will open up vi (or any editor defined in EDITOR env variable) and let you edit the parallel environment settings. To change from round_robin to fill_up in the above example, change the allocation_rule line from:
allocation_rule $round_robin
to:
allocation_rule $fill_up
After making the change and saving the file you can verify your settings using:
sgeadmin@ip-10-194-13-219:~$ 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 $fill_up
control_slaves TRUE
job_is_first_task FALSE
urgency_slots min
accounting_summary FALSE
The general workflow for running MPI code is:
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.
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 [...]