Install NVIDIA Graphics Driver:
sudo apt-get install nvidia-384 nvidia-modprobe
Download CUDA 9.0:
wget https://developer.nvidia.com/compute/cuda/9.0/Prod/local_installers/cuda_9.0.176_384.81_linux-run
Extract cuda_9.0.176_384.81_linux-run
:
chmod +x cuda_9.0.176_384.81_linux-run
./cuda_9.0.176_384.81_linux-run
Run:
sudo ./cuda-linux.9.0.176-22781540.run
sudo ./cuda-samples.9.0.176-22781540-linux.run
Configure the runtime library:
sudo bash -c "echo /usr/local/cuda/lib64/ > /etc/ld.so.conf.d/cuda.conf"
sudo ldconfig
Open /etc/environment
:
sudo nano /etc/environment
Append PATH
with :/usr/local/cuda/bin
in /etc/environment
file.
Install gcc-6
and g++-6
and link them with CUDA:
sudo apt-get install gcc-6 g++-6
sudo ln -s /usr/bin/gcc-6 /usr/local/cuda/bin/gcc
sudo ln -s /usr/bin/g++-6 /usr/local/cuda/bin/g++
Restart the computer:
reboot
Go to /usr/local/cuda-9.0/samples
:
cd /usr/local/cuda-9.0/samples
Run:
sudo make
If there are no errors and just warnings, installation is complete.
Go to https://developer.nvidia.com/rdp/cudnn-download.
Press Download cuDNN v7.X.Y, for CUDA 9.0.
Then press to download these selections:
- cuDNN Runtime Library for Ubuntu16.04 (Deb),
- cuDNN Developer Library for Ubuntu16.04 (Deb),
- cuDNN Code Samples and User Guide for Ubuntu16.04 (Deb).
Install downloaded files:
sudo dpkg -i libcudnn7_7.X.Y.Z-1+cuda9.0_amd64.deb
sudo dpkg -i libcudnn7-dev_7.X.Y.Z-1+cuda9.0_amd64.deb
sudo dpkg -i libcudnn7-doc_7.X.Y.Z-1+cuda9.0_amd64.deb
Copy cuDNN samples:
cp -r /usr/src/cudnn_samples_v7/ ~
Go to mnistCUDNN
folder:
cd ~/cudnn_samples_v7/mnistCUDNN
Compile and run:
make clean && make
./mnistCUDNN
If you see Test passed! at the end of the output then installation is complete.
Download Anaconda from https://www.anaconda.com/download/#linux.
Run installation:
chmod u+x Anaconda3-X.Y.Z-Linux-x86_64.sh
./Anaconda3-X.Y.Z-Linux-x86_64.sh
Close and open terminal.
Create Tensorflow environment for Python 3.6:
conda create -n tensorflow python=3.6
Activate environment:
conda activate tensorflow
Install TensorFlow GPU
version
pip install tensorflow-gpu