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From "wangwei (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SINGA-100) Implement layers using CUDNN for GPU training
Date Mon, 02 Nov 2015 13:24:27 GMT
wangwei created SINGA-100:
-----------------------------

             Summary: 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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