distributed models with RePast

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distributed models with RePast

Hazel Parry
Hi,
This relates to the previous email re RePast on a computational grid -
What facilities are available, if any, to aid the distribution of a
single RePast model across a number of nodes (e.g. distributing agents),
to improve memory availability and perhaps also efficiency?  Does anyone
know of simulations that have been developed in this way using RePast?
Does ProActive facilitate this?

I ask, because we have distributed agents from a single RePast
simulation at the university of leeds using MPIJava on a Beowulf
cluster, but are 'retrospectively' wondering what other examples are out
there?!

thanks very much,
Hazel

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Hazel Parry
Webpage: http://www.geog.leeds.ac.uk/people/h.parry
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Re: distributed models with RePast

Luc Girardin
Dear Hazel,

> This relates to the previous email re RePast on a computational grid -
> What facilities are available, if any, to aid the distribution of a
> single RePast model across a number of nodes (e.g. distributing agents),
> to improve memory availability and perhaps also efficiency?  Does anyone
> know of simulations that have been developed in this way using RePast?
> Does ProActive facilitate this?

> I ask, because we have distributed agents from a single RePast
> simulation at the university of leeds using MPIJava on a Beowulf
> cluster, but are 'retrospectively' wondering what other examples are out
> there?!

If the focus is on running one large simulation over many machines (more than one machine per simulation), then the only mechanism provided by RePast that I am aware of is the multi-threaded scheduling of actions (using Schedule.scheduleActionAt() with a duration longer than one), which should work on any SMP machine.

Beyond that, one could think about extending the current scheduling mechanism to execute actions concurrently on some machines, for example using ProActive. However, I am skeptical that one would gain any speedup (because of the network latency) if the agents need to interact (i.e. communicate or share a common space) with one another or if the computational load of a single agent is low... two properties of most agent-based models.

Take care,

Luc

--
Luc Girardin, Swiss Federal Institute of Technology (ETH)
Center for Comparative and International Studies (CIS)
Seilergraben 49, CH-8092 Zürich  Switzerland
http://www.icr.ethz.ch/



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Re: distributed models with RePast

North, Michael
In reply to this post by Hazel Parry

This is correct.  As a note, agent-based models with “thick” agents (i.e., agents that do a large amount of computation per action or step) can sometimes gain from distributed execution.  If you move objects to different machines, say with ProActive or raw RMI, with a little work can you use Repast's multithreaded scheduler to get distributed execution.  We've done some of this with RMI.  However, Luc's point about the need for substantial computation per agent is important.  The agents in most agent-based models  are too “thin” to benefit from this kind of distributed computation.

Mike


-----Original Message-----
From: [hidden email]
To: Hazel Parry
CC: [hidden email]
Sent: Tue Nov 15 09:24:45 2005
Subject: Re: [Repast-interest] distributed models with RePast

Dear Hazel,

> This relates to the previous email re RePast on a computational grid -
> What facilities are available, if any, to aid the distribution of a
> single RePast model across a number of nodes (e.g. distributing agents),
> to improve memory availability and perhaps also efficiency?  Does anyone
> know of simulations that have been developed in this way using RePast?
> Does ProActive facilitate this?

> I ask, because we have distributed agents from a single RePast
> simulation at the university of leeds using MPIJava on a Beowulf
> cluster, but are 'retrospectively' wondering what other examples are out
> there?!

If the focus is on running one large simulation over many machines (more than one machine per simulation), then the only mechanism provided by RePast that I am aware of is the multi-threaded scheduling of actions (using Schedule.scheduleActionAt() with a duration longer than one), which should work on any SMP machine.

Beyond that, one could think about extending the current scheduling mechanism to execute actions concurrently on some machines, for example using ProActive. However, I am skeptical that one would gain any speedup (because of the network latency) if the agents need to interact (i.e. communicate or share a common space) with one another or if the computational load of a single agent is low... two properties of most agent-based models.

Take care,

Luc

--
Luc Girardin, Swiss Federal Institute of Technology (ETH)
Center for Comparative and International Studies (CIS)
Seilergraben 49, CH-8092 Zürich  Switzerland
http://www.icr.ethz.ch/



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