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On Sean's question, we are working toward expanding models that will require 1.a (a coral reef grid full of agents that is too big or too slow if handled without parallelization), and possibly 1.b (3D corals, each of which are each made up of hundreds of polyps). We will be tying into Lattice Boltzmann and/or smoothed particle hydrodynamic models associated with both scales. All of the discussions recently of various options have been of interest, though an extension of Mason that would facilitate this would be of considerable assistance. Cheers! John McManus -----Original Message----- From: MASON Multiagent Simulation Toolkit [mailto:[log in to unmask]] On Behalf Of Sean Luke Sent: Friday, December 07, 2007 8:58 AM To: [log in to unmask] Subject: Re: cluster or grid parallelization There are three kinds of uses of parallelization here that I'd like to disambiguate: 0 Parallelizing an experiment within a single machine. 1. Parallelizing a single experiment by spreading it across multiple machines that work together. This commonly involves one or both of the following tasks. 1.a Distribute the *space* of the world across multiple machines because it's so big in memory 1.b Distribute the *agents* of the world because their computational cost is too large 2. Using multiple machines to do multiple experiments, one experiment per machine. #0 is trivial. For #2, shell scripts and rsh do just fine for us; indeed use of PVM/ MPI etc., is just way too heavyweight, particularly since Java and MPI don't play well together still. #2 is also very cleanly done on grid computing solutions. If anyone's interested, there's a company in my area (Parabon) which negotiates to borrow excess cycles on organizations' PCs and then sells this time with a Java-only piece of grid computing software. For a large NASA project they've adapted my ECJ code to this system and I'm sure would be interested in tasks you might have in MASON. Give 'em a call (parabon.com). For #1, I'm very interested in knowing how people are adapting MASON (or RePast) to distribute their experiment. Do you have 1.a as a need? 1.b? How are you going about hacking MASON etc. to do it? The reason I ask is that one of our grants may push us to look into creating a version of MASON which does #1 cleanly. Note that MASON was specifically designed for #2, and indeed *good*, efficient architectures are very different between #1 designs and #2 designs. So we're going to have to think about what kinds new data structures will we need. Probably at least we'll need a distributed schedule sync device, a way for agents to migrate, and several mechanisms for distributing space. It's a lot of overhead. I'm interested that some have mentioned RePast. RePast etc. weren't designed for #1 *or* #2. I know people have been hacking distribution onto RePast, and am interested in how they overcame the issue of the schedule containing single-machine Java events (repaints etc.). It might help inform us when we get to working on this. Sean