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https://issues.apache.org/jira/browse/SINGA-100?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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wangwei resolved SINGA-100.
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Resolution: Fixed
Resolved together with SINGA-88.
> 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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