To analyze data, we sometimes need to run over many thousands of runs at once. To do this in parallel, we can submit a job for every run we want to do. This will proceed in several steps:

1. We need to prepare an analysis program.
   1. This is demo.cxx.
   2. The program will take an input data file and an output location.
   3. The program will do some analysis on each events, and then write the result of that analysis to an output file labeled by the same number as the input file.
2. We need to prepare a job script for PBS.
   1. This is "run.sh"; this is the set of instructions to be submitted to the cluster.
   2. The instructions say to:
      1. Source a a shell environment
      2. To run the executable
      3. Move the output root file to the output location.
   3. Note that we're telling the program we wrote in step 1 to write to the node-local $TMPDIR, and then moving the result to our final output directory at the end. This is better for cluster performance.
3. We need to make a list of data files to run over
   1. We can do this on OSC by running ls -d -1 /fs/scratch/PAS0654/ara/10pct/RawData/A3/2013/sym_links/event*.root > run_list.txt
   2. This places the full path to the ROOT files in that folder into a list called run_list.txt that we can loop over.
4. Third, we need to script that will submit all of the jobs to the cluster.
   1. This is "submit_jobs.sh".
   2. This loops over all the files in our run_list.txt and submits a run.sh job for each of them.
   3. This is also where we define the $RUNDIR (where the code is to be exeucted) and the $OUTPUTDIR (where the output products are to be stored)

Once you've generated all of these output files, you can run over the output files only to make plots and such.