Ubuntu Tensorflow GPU

• 1. get the permission of a folder
     sudo chmod a+rwx /szDirectoryName
• 2. GPU installation:
     Nvidia driver 384

sudo add-apt-repository -y ppa:graphics-drivers/ppa
sudo apt-get update
sudo apt-get install -y nvidia-367

CUDA Toolkit 9.0, https://developer.nvidia.com/cuda-downloads

sudo chmod u+x cuda_9.0.61_375.26_linux-run
./cuda_9.0.61_375.26_linux-run

Do you accept the previously read EULA?
accept/decline/quit: accept
Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 361.77?
(y)es/(n)o/(q)uit: n
Install the CUDA 8.0 Toolkit?
(y)es/(n)o/(q)uit: y
Enter Toolkit Location
[ default is /usr/local/cuda-8.0]: enter
Do you want to install a symbolic link at /usr/local/cuda?
(y)es/(n)o/(q)uit:y
Install the CUDA 8.0 Samples?
(y)es/(n)o/(q)uit:y
Enter CUDA Samples Location
[ defualt is /home/kylebai ]: enter

When complete
gedit ./bashrc
adding following at the end:

export PATH=${PATH}:/usr/local/cuda-9.0/bin
export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64

Now you can type nvidia-smi

Installing cuDNN 7.0 https://developer.nvidia.com/rdp/cudnn-download

tar -zxvf cudnn-9.0-linux-x64-v7.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
sudo chmod a+r /usr/local/cuda/lib64/libcudnn*

• 3. Anaconda:

export PATH=~/anaconda3/bin:$PATH

conda create -n tf-gpu python=3.5 anaconda

• 4. Tensorflow-gpu
     pip install tensorflow-gpu
• 5. Install [Brightness Controller] https://github.com/lordamit/Brightness

sudo add-apt-repository ppa:apandada1/brightness-controller
sudo apt update

For Version 1 with up to 4 Monitor Support:

sudo apt install brightness-controller-simple