Hexo

Upgrade cuda & tensorflow

Step 1: Remove previous cuda completely

1. To uninstall the CUDA Toolkit, run the uninstallation script provided in the bin directory of the toolkit. By default, it is located in /usr/local/cuda-7.5/bin:
   $ sudo /usr/local/cuda-7.5/bin/uninstall_cuda_7.5.pl

run the uninstall script in /usr/local/cuda-9.2/bin

2. To uninstall the NVIDIA Driver, run nvidia-uninstall:
   $ sudo nvidia-uninstall

3. Remove all nvidia drivers completely
   sudo apt-get autoremove –purge nvidia-*

Step 2: Install Cuda Toolkit

0. Description: Toolkit contains

   1. NVIDIA Accelerated Graphics Driver
   2. OpenGL libraries
   3. CUDA 8.0 Toolkit

1. Hit CTRL+ALT+F1 and login using your credentials.

2. kill your current X server session by typing sudo service lightdm stop or sudo lightdm stop

3. Enter runlevel 3 by typing sudo init 3 and install your .run file.
   Run sudo sh cuda_8.0.44_linux.run

4. You might be required to reboot when the installation finishes.
   If not, run sudo service lightdm start or sudo start lightdm to start your X server again.

Step 3: Environment Setup

• export PATH=/usr/local/cuda/bin:$PATH
• export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH

Step 4: Install CuDNN

1. download CuDNN from https://developer.nvidia.com/cudnn

2. Uncompress and copy the cuDNN files into the toolkit directory. Assuming the toolkit is
   installed in /usr/local/cuda, run the following commands

   tar xvzf cudnn-8.0-linux-x64-v5.1-ga.tgz
   sudo cp cuda/include/cudnn.h /usr/local/cuda/include
   sudo cp cuda/lib64/libcudnn /usr/local/cuda/lib64
   sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn

Step 5: Upgrade tensorflow

1. Ubuntu/Linux 64-bit, GPU enabled, Python 2.7
   Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see “Installing from sources” below.
   $ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-0.12.0-cp27-none-linux_x86_64.whl

2. $ sudo pip install –upgrade $TF_BINARY_URL