[
https://issues.apache.org/jira/browse/SINGA-109?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15041488#comment-15041488
]
ASF subversion and git services commented on SINGA-109:
-------------------------------------------------------
Commit bd2e3453ca01e7bf9bf6724b4717d956c6e00290 in incubator-singa's branch
refs/heads/master from WANG Sheng
[ https://git-wip-us.apache.org/repos/asf?p=incubator-singa.git;h=bd2e345 ]
SINGA-109 Refine bridge layers
re-implement bridge layers for model partition
* move socket operations for sending/receiving blobs from worker into layers,
so that it is transparent to users who will implment TrainOneBatch
* when initialing worker, it will create a socket instance and pass it to all
bridge layers using layer.MakePaired() function
> Refine bridge layers for inter-node layer communication
> -------------------------------------------------------
>
> Key: SINGA-109
> URL: https://issues.apache.org/jira/browse/SINGA-109
> Project: Singa
> Issue Type: Improvement
> Reporter: Sheng Wang
> Assignee: Sheng Wang
>
> Previously, sending data and gradient blobs between remote bridge layers is
> explicitly handled by worker.
> Train One Batch functions need to manage sending/receiving data before doing
> real work.
> This ticket is to encapsulate bridge layer communications, and put them
> inside their own compute feature/gradient functions.
> So that the worker do not need to know how the neuralnet is partitioned and
> communicated.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
