Tuesday Exercise 1.3: Running jobs in the OSG

The goal of this exercise is to have your jobs running on the OSG and map their geographical locations.

Where in the world are my jobs? (Part 2)

In this version of the geolocating exercise, you will submit jobs to the OSG from osg-learn.chtc.wisc.edu and hopefully getting back much more interesting results! You will be using the same exact payload as you did in exercise 1.1.

Gathering network information from the OSG

Now to create submit files that will run in the OSG!

  1. If not already logged in, ssh into osg-learn.chtc.wisc.edu
  2. Make a new directory for this exercise, tuesday-1.3 and change into it
  3. Use scp or rsync from exercise 1.2 to copy over the executable and input file from the tuesday-1.1 directory from learn.
  4. Re-create the submit file from exercise 1.1 except this time around change your submit file so that it submits five hundred jobs!
  5. Submit your file and wait for the results

Mapping your jobs

As before, you will be using http://www.mapcustomizer.com/ from osg-learn.chtc.wisc.edu to visualize where your jobs have landed in the OSG. Copy and paste the collated results from your job output into the bulk creation text box at the bottom of the screen. Where did your jobs end up?

Extra Challenge: Cleaning up your submit directory

If you run ls in the directory from which you submitted your job, you may see that you now have thousands of files! Proper data management starts to become a requirement as you start to develop truly HTC workflows; you'll want organize your submit files, code, and input data separate from your output data.

  1. Try editing your submit file so that all your output and error files are saved to separate directories within your submit directory.

    Tip

    Experiment with fewer job submissions until you're confident you have it right, then go back to submitting 1000 jobs!

  2. Submit your file and track the status of your jobs.

Did your jobs complete successfully with output and error files saved in separate directories? If not, can you find any useful information in the job logs or hold messages? If you get stuck, review Monday's slides on submitting many jobs.

Extra Challenge: Running it all as a DAG

Yesterday, you learned about DAGs and you can take advantage of them to avoid collating the output data by hand. Try writing a one node dag with a POST script that collates the latitude/longitude values from your output files.

If you are not familiar with writing scripts, here are some short instructions for writing a simple bash script that can be used as a POST script:

  1. Write a file with a .sh extension

  2. Add a bash "shebang" line to the top of the script and lines for each shell command that you'd like to run (imagine it as a terminal in file form). For example, the following shell script would create a directory foo then list its contents:

    #!/bin/bash
mkdir foo
ls foo

  3. Mark the script as executable

  4. Run it by hand to verify that it works