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From Nicolas Lalevée <>
Subject Re: Custom halt condition
Date Tue, 02 Apr 2013 22:50:22 GMT

Le 29 mars 2013 à 15:04, Maja Kabiljo <> a écrit :

> Hi Nicolas,
> You are right, using aggregators and master compute is the way to go.
> Please take a look at
> to learn more about aggregators. From the MasterCompute.compute() you will
> be calling haltComputation() when you decided it's time to do so.

Thank you very much for that doc. For some reason I didn't found it previously.
The implementation is indeed straight forward. I'll need now to test it.


> Please let me know if you have any questions.
> Maja
> On 3/29/13 3:16 AM, "Nicolas Lalevée" <> wrote:
>> Hi,
>> In my use case (implementation of affinity propagation) I want to halt
>> the computation if at least of minimum of vertex has voted to halt. As
>> far as I understand the default is to halt if all vertex has voted to
>> halt and no messages are sent between vertices. But in my use case, even
>> if a vertex has voted to halt, it must sent and receive message in case
>> there is a next superstep. And with some of my data, some vertex makes a
>> lot of superstep to converge and vote to halt. Which I don't care much if
>> there are a little percentage of theses.
>> My current implementation create a fake "master" vertex which is
>> gathering the convergence of all vertices via messages. And once that
>> master decide it is time to halt the computation, it sends a message to
>> all vertices so they all halt.
>> But I have seen some thread here about some master compute, I have seen
>> some code about aggregators, so I guess there is some smarter way of
>> implementing this ?
>> Nicolas

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