This is the Installation guide for the overall repository.
GIGABYTE based BIOS setting
- First, DO NOT PLUG IN your GPU until the driver is set up.
- Internal Graphic : Auto > Enable
- Display Priority : PCIe > Internal
NVIDIA driver download .run file : click here
If you click download from the above site, you will get a .run file format for installing drivers.
Before you run the .run file, you first need to stop your Xserver display manager.
Press [Ctrl] + [Alt] + [F1], enter the script below
$ service --status-all | grep dm
(Result) [+] [:dm]
The part described as [:dm] is your display manager.
Substitute the [:dm] part below with the result of the script above.
$ sudo service [:dm] stop
(Result) * Stopping Light Display Manager [:dm]
Run the code below. Press 'Yes' for every option they ask.
$ sh <DIR where you downloaded the .run file>/NVIDIA-Linux_x86_64-375.20.run
After you have successfully installed, you shall see the same results when typing the code below.
$ nvidia-smi
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 375.20 Driver Version: 375.20 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 TITAN X (Pascal) Off | 0000:4B:00.0 Off | N/A |
| 67% 86C P2 249W / 250W | 5026MiB / 12221MiB | 82% Default |
+-------------------------------+----------------------+----------------------+
| 1 TITAN X (Pascal) Off | 0000:4C:00.0 On | N/A |
| 88% 90C P2 225W / 250W | 3842MiB / 12213MiB | 78% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
$ sudo reboot
You can skip the step above and automatically install the driver within CUDA installation.
Check the details below.
CUDA download page : click here
Before executing the file, stop the display manager by following the description above.
$ sudo sh <DIR where you downloaded the .run file>/cuda_8.0.44_linux.run
$ sudo apt-get install vim
$ git clone https://github.com/amix/vimrc.git ~/.vim_runtime
# Awesome version
$ sh ~/.vim_runtime/install_awesome_vimrc.sh
# Basic version
$ sh ~/.vim_runtime/install_basic_vimrc.sh
Open your ~/.bashrc file.
vi ~/.bashrc
# Press Shift + G, Add the lines on the bottom
export PATH=$PATH:/usr/local/cuda/bin
export LD_LIBRARY_PATH=/usr/local/cuda/lib64
export CUDA_HOME=/usr/local/cuda
To check if the CUDA toolkit is successfully installed, type the line below.
$ nvcc --version
* (Result)
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2016 NVIDIA Corporation
Built on Sun_Sep__4_22:14:01_CDT_2016
Cuda compilation tools, release 8.0, V8.0.44
cuDNN download page : click here
(Membership is required, just sign in!)
Download the newest cuDNN v5.1.
$ cd <DOWNLOAD DIR>
$ tar -zxvf ./cudnn-8.0-linux-x64-v5.1.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*
Tensorflow install page : click here
$ sudo apt-get install python-pip python-dev
$ pip install --upgrade pip
$ pip install tensorflow-gpu
Torch install page : click here
$ git clone https://github.com/torch/distro.git ~/torch --recursive
$ cd ~/torch; bash install-deps;
$ ./install.sh
$ source ~/.bashrc