Mailing-List: contact dev-help@giraph.apache.org; run by ezmlm
Precedence: bulk
Reply-To: dev@giraph.apache.org
Date: Tue, 15 Jan 2013 13:44:13 +0000 (UTC)
From: "Sebastian Schelter (JIRA)" <jira@apache.org>
To: giraph-dev@incubator.apache.org
Message-ID: <JIRA.12627644.1358257272459.137131.1358257453341@arcas>
In-Reply-To: <JIRA.12627644.1358257272459@arcas>
References: <JIRA.12627644.1358257272459@arcas>
Subject: [jira] [Updated] (GIRAPH-480) Add convergence detection to
 org.apache.giraph.examples.RandomWalkVertex
MIME-Version: 1.0
Content-Type: text/plain; charset=utf-8
Content-Transfer-Encoding: 7bit


     [ https://issues.apache.org/jira/browse/GIRAPH-480?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sebastian Schelter updated GIRAPH-480:
--------------------------------------

    Description: 
I propose to add convergence detection to the RandomWalkVertex. Convergence is achieved when the overall absolute change (L1 norm) of the difference between the current and the previous probability vector becomes less than a given threshold. Convergence detection can be implemented via an additional aggregator and a check in the master compute function.

This change would make the class much easier to use as the users don't have to worry about the number of supersteps to execute, but can simply specify a high number as MAX_SUPERSTEPS and be sure that the algorithm convergences when acceptable quality of the result is reached.

  was:
I propose to add convergence detection to the RandomWalkVertex. Convergence is achieved when the overall absolute change (L1 norm) of the difference between the current and the previous probability vector. Convergence detection can be implemented via an additional aggregator.

This change would make the class much easier to use as the users don't have to worry about the number of supersteps, but can simply specify a high number as MAX_SUPERSTEPS and be sure that the algorithm convergences when acceptable quality of the result is reached.

    
> Add convergence detection to org.apache.giraph.examples.RandomWalkVertex
> ------------------------------------------------------------------------
>
>                 Key: GIRAPH-480
>                 URL: https://issues.apache.org/jira/browse/GIRAPH-480
>             Project: Giraph
>          Issue Type: Improvement
>          Components: examples
>    Affects Versions: 0.2.0
>            Reporter: Sebastian Schelter
>            Assignee: Sebastian Schelter
>
> I propose to add convergence detection to the RandomWalkVertex. Convergence is achieved when the overall absolute change (L1 norm) of the difference between the current and the previous probability vector becomes less than a given threshold. Convergence detection can be implemented via an additional aggregator and a check in the master compute function.
> This change would make the class much easier to use as the users don't have to worry about the number of supersteps to execute, but can simply specify a high number as MAX_SUPERSTEPS and be sure that the algorithm convergences when acceptable quality of the result is reached.

--
This message is automatically generated by JIRA.
If you think it was sent incorrectly, please contact your JIRA administrators
For more information on JIRA, see: http://www.atlassian.com/software/jira