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This issue tracks full cuDNN4 support with rust-cudnn.
cuDNN 4 does not introduce many new things and rust-cudnn works already pretty well with the cuDNN 4 library. (see notable update below) Mostly it makes improvements to the Normalization API and internally improves the convolution performance. From the cuDNN 4 release notes.
_New Features_
- Batch Normalization routines have been added.
- Convolution forward and backward now supports NHWC tensor format.
- FFT Tiling algorithm has been added for cudnnConvolutionForward and cudnnConvolutionBackwardData routines
- cudnnConvolutionForward now supports computation in FP16 when run on GPU
with a compute capability >= 5.3
- cudnnConvolutionForward has been optimized for batch size = 1
- Pooling and activation routines have a descriptor option to propagate NaN numbers.
One notable update of cuDNN 4 is
Performance of cudnnConvolutionBackwardFilter when using Algo 1 has been
improved for some cases. This code path now also requires a workspace.
which affects collenchyma-nn as it makes the convolution algorithm inconsistent when switching from cuDNN3 to cuDNN4.
The text was updated successfully, but these errors were encountered:
#21 adds "passive" cuDNNv4 support, meaning that it knows about the FFT Tiling algorithm, so it won't break when cuDNNv4 is used, but doesn't implement any of the other new features.
This issue tracks full cuDNN4 support with rust-cudnn.
cuDNN 4 does not introduce many new things and rust-cudnn works already pretty well with the cuDNN 4 library. (see notable update below) Mostly it makes improvements to the Normalization API and internally improves the convolution performance. From the cuDNN 4 release notes.
One notable update of cuDNN 4 is
which affects collenchyma-nn as it makes the convolution algorithm inconsistent when switching from cuDNN3 to cuDNN4.
The text was updated successfully, but these errors were encountered: