As usual after a day of writing, I needed to take a break. I decided to watch an old webinar on the Eclipse communications project. Why does a psychologist/roboticist care about a platform specific communications system? Aside from the possibilities of leveraging others work on shared editing, or even chat/IM within the IDE (great for contacting me if you’ve got a question), it also opens the door to more effective distributed model execution.

As cognitive modelers we routinely have to run thousands of model iterations in order to collect enough data to do effective quantitative fits. For simple models, the time cost is negligible, but larger models can serious tax computation resources for quite sometime. My dissertation experiments lasted around two hours, and the model runs took almost 15 minutes per simulated subject. Given the parameter space I had to explore, it was common for my machine to be bogged down for days on end. My solution at the time was to VNC into other machines in the lab, update the model from SVN, then run a set of parameters. Not the most effective distribution mechanism.

Wouldn’t it be better if you could do all this from the IDE without any hassle? Imagine if you could specify the bulk model executions and then farm it out to a set of machines without any heavy lifting or sacrificing your processor cycles. The combination of OSGi bundles (which all jACT-R models are), Eclipse’s PDE, and ECF makes this possibility a very near reality (p2 will definitely help too as it will make enforcing consistent bundle states much easier).

After watching the webinar I couldn’t resist and started building the pieces. Here’s how the bad-boy will work:

  1. define the run configuration for the iterative model run
  2. then select the remote tab which will list all the discovered service capable of accepting the model run (pruned based on dependencies of your model)
  3. the model and all its dependencies is exported to a zip file and sent to the remote service
  4. the remote service unpacks, imports and compiles the content (ensuring that all the deps are met and your code will actually run) – it then executes the run configuration
  5. as the execution progresses, the service transmits the state information back to your IDE (i.e. iteration #, ETA, etc)
  6. when all is done, it packages up the working directory that the model was run in and sends it back
  7. this is then expanded into your runs/ directory as if you had executed the bulk run yourself.

This is actually a sloppy implementation of a more general functionality that Eclipse might find useful: transmitting local bundles and invoking them on a remote system.

I’ve got a weekend away from distractions coming up and I think I can get a rough implementation working by then. This will certainly make the bulk monkey runs go so much easier (remote desktop is usable but really just too much of a hassle). Of course, I could use that time to work on the spatial modeling instead.. but that’s too much like real work for a weekend.