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From "ASF subversion and git services (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SINGA-100) Implement layers using CUDNN for GPU training
Date Thu, 17 Dec 2015 11:32:46 GMT

    [ https://issues.apache.org/jira/browse/SINGA-100?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15061931#comment-15061931
] 

ASF subversion and git services commented on SINGA-100:
-------------------------------------------------------

Commit b0033533d32c3eebf08f6cb4817cdc7389b9ebd0 in incubator-singa's branch refs/heads/master
from WANG Sheng
[ https://git-wip-us.apache.org/repos/asf?p=incubator-singa.git;h=b003353 ]

SINGA-100 Implement layers using CUDNN for GPU training

fix a bug in stub.cc


> Implement layers using CUDNN for GPU training
> ---------------------------------------------
>
>                 Key: SINGA-100
>                 URL: https://issues.apache.org/jira/browse/SINGA-100
>             Project: Singa
>          Issue Type: New Feature
>            Reporter: wangwei
>
> NVIDIA has released the cudnn library optimized for CNN operations like convolution,
pooling, etc. It has achieved overall good performance. Hence, it is essential to add cudnn
supported layers in SINGA for efficient GPU training (SINGA-41).
> We will use the cudnn library to implement CNN layers, namely,
>  cudnnConvolutionLayer, cudnnPoolingLayer, cudnnLRNLayer, cudnnSoftmaxLayer, cudnnReLULayer,
cudnnSigmoidLayer, cudnnTanhLayer, cudnnDivNormLayer.
> Data type float-16 will not be consider in this ticket.



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