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https://issues.apache.org/jira/browse/SINGA-100?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15059895#comment-15059895
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ASF subversion and git services commented on SINGA-100:
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Commit 6f81adba402bcd217dd020faa4188968b3200bb7 in incubator-singa's branch
refs/heads/master from [~zhongle]
[ https://git-wip-us.apache.org/repos/asf?p=incubator-singa.git;h=6f81adb ]
SINGA-100 Implement layers using CUDNN for GPU training
Fixs include path problems on cudnn.
A reminder:
Users should configure their library path(LD_LIBRARY_PATH & LIBRARY_PATH) after
they install cudnn libs.
> 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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