Condor

There's two fundamental steps to using condor.

  1. Writing a condor submit script
  2. Submitting it with condor_submit

You should run  condor_submit my_script.condor  on pongo.cacr.caltech.edu

The other most useful Condor commands are:

technically  condor_q   only looks at the current computer, which is why we launch everything from pongo)

Writing a script

There's a fair amount of boiler-plate text that goes into a condor script. Here's close to the simplest example

universe=vanilla
executable=/usr/bin/python
output=script.output
error=script.output
log=script.log

arguments=script.py --do_that_thing
queue

the important parts are:

You can list argument / queue multiple times -- this will tell condor that there are multiple "processes" that you want to have run.

The log file will give information about where the program is running and if it aborted for some reason. The output file contains the standard output from the program, the error file contains the standard error. If you list the same file for both it'll end up looking like you ran the program on a terminal with both normal output and error output mixed together.

More Information

The condor user documentation is at http://research.cs.wisc.edu/htcondor/manual/v7.8/index.html

A tutorial presentation (.ppt) and Videos from the 2008 Condor Week Presentations.

If you have a multi-threaded application (like bowtie) or an application that starts subprosess (like tophat) you'll need to tell condor how many cpus you expect to use. Most of the examples in /Templates illustrate how to use the request_cpu, request_memory, and request_disk parameters. If you're running a large program you'll want to set those so condor doesn't kill your job for exceeding the capabilities of the machine you're running on.


Distributed computing in practice:the Condor experience is a paper describing the history and goals of the Condor project.

WoldlabWiki: Condor (last edited 2014-07-15 21:33:54 by diane)