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From "Edward J. Yoon (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HORN-2) Umbrella ticket for Implementation Planning of Apache Horn
Date Tue, 20 Oct 2015 04:29:27 GMT

    [ https://issues.apache.org/jira/browse/HORN-2?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14964496#comment-14964496
] 

Edward J. Yoon commented on HORN-2:
-----------------------------------

Few things I'd like to share with you:

1) Without big changes, I think we can refactor the legacy source code to neuron-centric framework.
The main advantage of this programming APIs that we will be able to divide partitions based
on neuron and parallelize its calculations (internally) and have more intuitive programming
model.

2) We might want to have pluggable design for computing engine in the future, so that we sit
not only on Hama but also REEF or Spark. 

> Umbrella ticket for Implementation Planning of Apache Horn
> ----------------------------------------------------------
>
>                 Key: HORN-2
>                 URL: https://issues.apache.org/jira/browse/HORN-2
>             Project: Apache Horn
>          Issue Type: Wish
>            Reporter: Edward J. Yoon
>
> My old rough idea is described here: http://blog.udanax.org/2015/06/googles-distbelief-clone-project-on.html
> The basic idea of data and model parallelism is use of the remote parameter server to
parallelize model creation and distribute training across machines, and the region barrier
synchronization per task group instead of global barrier synchronization for performing asynchronous
mini-batches within single BSP job.
> Since Apache Hama provides pluggable interface for Synchronization[1], we can easily
create our own region barrier synchronization service for handling multiple BSP worker groups
(Regarding management of Tasks Topology, I have no concrete idea yet).
> Parameter Server requires decision whether to use Legacy open source or implement ourself.
> My rough Programming Inteface Design is only focused on feed-forward networks such as
MLP, CNN, and Autoencoder. We may want to conver everything.
> 1. http://wiki.apache.org/hama/SyncService



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