http://developer.nvidia.com/rdp/cudnn-download
要先登入下載：
cuDNN v7.3.1 Library for Linux
cuDNN v7.3.1 Runtime Library for Ubuntu18.04 (Deb)
cuDNN v7.3.1 Developer Library for Ubuntu18.04 (Deb)
cuDNN v7.3.1 Code Samples and User Guide for Ubuntu18.04 (Deb)
先解壓縮然後將檔案放入cuda：
- tar -xvf cudnn-10.0-linux-x64-v7.3.1.20.tgz
- sudo cp cuda/include/cudnn.h /usr/local/cuda/include/
- sudo cp cuda/lib64/lib* /usr/local/cuda/lib64/
- cd /usr/local/cuda/lib64/
- sudo chmod +r libcudnn.so.7.3.1
- sudo ln -sf libcudnn.so.7.3.1 libcudnn.so.7
- sudo ln -sf libcudnn.so.7 libcudnn.so
- sudo ldconfig
檢查是否安裝正確：
- sudo dpkg -i libcudnn7_7.3.1.20-1+cuda10.0_amd64.deb
- sudo dpkg -i libcudnn7-dev_7.3.1.20-1+cuda10.0_amd64.deb
- sudo dpkg -i libcudnn7-doc_7.3.1.20-1+cuda10.0_amd64.deb
- cp -r /usr/src/cudnn_samples_v7/ $HOME
- cd $HOME/cudnn_samples_v7/mnistCUDNN
- make clean && make
- ./mnistCUDNN
cudnnGetVersion() : 7301 , CUDNN_VERSION from cudnn.h : 7301 (7.3.1)
Host compiler version : GCC 7.4.0
There are 1 CUDA capable devices on your machine :
device 0 : sms 4 Capabilities 3.0, SmClock 928.0 Mhz, MemSize (Mb) 978, MemClock 2700.0 Mhz, Ecc=0, boardGroupID=0
Using device 0
Testing single precision
Loading image data/one_28x28.pgm
Performing forward propagation ...
Testing cudnnGetConvolutionForwardAlgorithm ...
Fastest algorithm is Algo 2
Testing cudnnFindConvolutionForwardAlgorithm ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: 0.022368 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: 0.033792 time requiring 100 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: 0.038592 time requiring 57600 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: 0.182528 time requiring 203008 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: 0.476448 time requiring 2057744 memory
Resulting weights from Softmax:
0.0000000 0.9999399 0.0000000 0.0000000 0.0000561 0.0000000 0.0000012 0.0000017 0.0000010 0.0000000
Loading image data/three_28x28.pgm
Performing forward propagation ...
Resulting weights from Softmax:
0.0000000 0.0000000 0.0000000 0.9999288 0.0000000 0.0000711 0.0000000 0.0000000 0.0000000 0.0000000
Loading image data/five_28x28.pgm
Performing forward propagation ...
Resulting weights from Softmax:
0.0000000 0.0000008 0.0000000 0.0000002 0.0000000 0.9999820 0.0000154 0.0000000 0.0000012 0.0000006
Result of classification: 1 3 5
Test passed!
Testing half precision (math in single precision)
Loading image data/one_28x28.pgm
Performing forward propagation ...
Testing cudnnGetConvolutionForwardAlgorithm ...
Fastest algorithm is Algo 2
Testing cudnnFindConvolutionForwardAlgorithm ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: 0.031456 time requiring 100 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: 0.034304 time requiring 28800 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: 0.040608 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: 0.144544 time requiring 207360 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: 0.167264 time requiring 203008 memory
Resulting weights from Softmax:
0.0000001 1.0000000 0.0000001 0.0000000 0.0000563 0.0000001 0.0000012 0.0000017 0.0000010 0.0000001
Loading image data/three_28x28.pgm
Performing forward propagation ...
Resulting weights from Softmax:
0.0000000 0.0000000 0.0000000 1.0000000 0.0000000 0.0000714 0.0000000 0.0000000 0.0000000 0.0000000
Loading image data/five_28x28.pgm
Performing forward propagation ...
Resulting weights from Softmax:
0.0000000 0.0000008 0.0000000 0.0000002 0.0000000 1.0000000 0.0000154 0.0000000 0.0000012 0.0000006
Result of classification: 1 3 5
Test passed!
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