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https://issues.apache.org/jira/browse/SINGA-235?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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wangwei closed SINGA-235.
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Resolution: Fixed
> Unify the engines for cudnn and singa layers
> --------------------------------------------
>
> Key: SINGA-235
> URL: https://issues.apache.org/jira/browse/SINGA-235
> Project: Singa
> Issue Type: Improvement
> Reporter: wangwei
>
> For most layers, we would have multiple implementations, e.g., using cudnn
> for nvidia gpu, using cpp for cpu and using opencl for other gpus.
> These layers have different classes. They are registered with different
> identifiers. This ticket would unify the layer identifiers for each engine:
> 1. cudnn layers are registered with identifier = cudnn_xxx, e.g.,
> cudnn_convolution for the CudnnConvolution layer.
> 2. singa layers are registered with identifier = singa_xxx, e.g.,
> singa_convolution for the Convolution layer.
> cudnn engine must run on cuda devices. and singa engine could run on cuda-gpu
> device or cpp-cpu device depending on the layer type. For instance, the
> Convolution layer must run on cpp-cpu device, and Dense layer can run on both
> devices and would select the correct device automatically.
> Users need to make sure the engine and the device of the tensors.
> Both CPP and Python code is updated. Users have to compose the layer
> identifier manually for CPP version. For Python version, users can set
> layer.engine='cudnn' or 'singa'.
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