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mburakergenc / TensorFlow-with-GPU-on-Ubuntu16.04

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Guide to installing TensorFlow with GPU Support on Ubuntu 16.04

  • Install NVIDIA Drivers and restart your computer
$ sudo add-apt-repository ppa:graphics-drivers/ppa
$ sudo apt-get update
$ sudo ubuntu-drivers autoinstall
$ reboot

After restarting go to

System Settings -> Software & Updates -> Additional Drivers

select Using NVIDIA - version 361.42 from nvidia-361

Because the toolkit uses an older driver, select **No** to driver.
Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 352.39? ((y)es/(n)o/(q)uit): N
Install the CUDA 7.5 Toolkit? ((y)es/(n)o/(q)uit): Y
Enter Toolkit Location [ default is /usr/local/cuda-7.5 ]:
you want to install a symbolic link at /usr/local/cuda? ((y)es/(n)o/(q)uit): Y
Install the CUDA 7.5 Samples? ((y)es/(n)o/(q)uit): N

Then, wait for installation to complete. Ignore the warning that you will get for the drivers at the end of the installation.

$ mv cuda cudnn
$ sudo cp cudnn /usr/local

Then create symlinks in /usr/local/cuda/lib64 to /usr/local/cudnn/lib64

$ sudo ln -s /usr/local/cuda/lib64/libcudnn.so /usr/local/cudnn/lib64/libcudnn.so
$ sudo ln -s /usr/local/cuda/lib64/libcudnn.so.4 /usr/local/cudnn/lib64/libcudnn.so.4
$ sudo ln -s /usr/local/cuda/lib64/libcudnn.so.4.0.7 /usr/local/cudnn/lib64/libcudnn.so.4.0.7
$ sudo ln -s /usr/local/cuda/lib64/libcudnn_static.a /usr/local/cudnn/lib64/libcudnn_static.a
  • Set up bashrc
$ sudo nano ~/.bashrc
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cudnn/lib64
export CUDA_HOME=/usr/local/cuda
export PATH=/usr/local/cuda/bin:$PATH
  • Add environment variables
$ sudo nano /etc/profile.d/cuda.sh
export PATH=$PATH:/usr/local/cuda/bin
$ sudo nano /etc/ld.so.conf.d/cuda.conf
/usr/local/cuda/lib64
$ sudo nano /etc/ld.so.conf.d/cudnn.conf
/usr/local/cudnn/lib64
$ sudo ldconfig
$ source ~/.bashrc
  • Force it to work with gcc 5 
$ sudo nano /usr/local/cuda/include/host_config.h
line: 115 comment out error
//#error -- unsupported GNU version! gcc versions later than 4.9 are not supported!
  • Verify your driver and installation
$ nvidia-smi
$ nvcc -V
$ which nvcc
  • Download Anaconda for either Python 2.7 or 3.5 (I will use 2.7)
[Download from here](https://www.continuum.io/downloads)
$ bash Anaconda2-4.1.1-Linux-x86_64.sh
  • Download TensorFlow and create a TensorFlow environment using Python 2.7
$ conda create -n tensorflow python=2.7
$ wget https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.10.0-cp27-none-linux_x86_64.whl
  • Finally start the TensorFlow environment
$ source activate tensorflow
(tensorflow) $ pip install --ignore-installed --upgrade tensorflow-0.10.0-cp27-none-linux_x86_64.whl

To exit the env

(tensorflow) $ source deactivate

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