SAGA Tutorial Part 3: Remote Job Submission

In this second part of the tutorial, we take the previous example and modify it, so that our job is executed on a remote machine instead of localhost. This second examples shows one of the most important capabilities of SAGA: abstracting system heterogeneity. We can use the same code we have used to run a job via 'fork' with minimal modifications to run a job on a completely different system, e.g., via 'ssh' or even 'pbs'.

Prerequisites

This example assumes that you have SSH access to a remote resource, either a single host (e.g., a cloud VM) or an HPC cluster. Alternatively, you can run an SSH server on your local machine to 'emulate' a remote resource.

The example also assumes that you have a working public/private SSH key-pair and that you can log-in to your remote resource of choice using those keys, i.e., your public key is in the ~/.ssh/authorized_hosts file on the remote machine. If you are not sure how this works, you might want to read SSH and GSISSH first.

Hands-On: Remote Job Submission

Copy the code from the previous example to a new file saga_example_2.py. To change the execution host for the job, change the URL in the job.Service constructor. If you want to use a remote SSH host, use a ssh://... URL:

js = saga.job.Service("ssh://remote.host.net")

Alternatively, if you have access to a PBS cluster, use a pbs+ssh://... URL:

js = saga.job.Service("pbs+ssh://remote.hpchost.net")

There are more URL options. Have a look at the Plugins page for a complete list. If you submitting your job to a PBS cluster, you will probably also have to make some modifications to your job.Description. Depending on the configuration of your cluster, you might have to put in the name of the queue you want to use or the allocation or project name that should be credited:

jd = saga.job.Description()

jd.environment     = {'MYOUTPUT':'"Hello from Bliss"'}       
jd.executable      = '/bin/echo'
jd.arguments       = ['$MYOUTPUT']
jd.output          = "my1stjob.stdout"
jd.error           = "my1stjob.stderr"

jd.queue           = "short" # Using a specific queue 
jd.project         = "TG-XYZABCX" # Example for an XSEDE/TeraGrid allocation

Save the file and execute it via the python interpreter (make sure your virtualenv is activated):

python saga_example_1.py

The output should look something like this:

Job ID    : [pbs+ssh://remote.hpchost.net]-[None]
Job State : saga.job.Job.New

...starting job...

Job ID    : [pbs+ssh://remote.hpchost.net]-[644240]
Job State : saga.job.Job.Pending

...waiting for job...

Job State : saga.job.Job.Done
Exitcode  : None

Once the job has completed, you can have a look at the output file my1stjob.stdout.

Note: Because you're working on a local system instead of submitting to a job cluster, the job state will immediately go to "Running" instead of "Pending." This is because your machine does not have to wait to start executing the job. In a similar way, the exitcode will most likely be "0" instead of "None." This is because your machine is actually returning "0" as the exitcode, whereas some SGE clusters won't return any exitcode at all.

Details & Discussion

---

Back: [Tutorial Home](SAGA Tutorial)    Next: SAGA Tutorial Part 4: XYZ