We generally followed the instructions in Setting up a Deep Learning Machine from Scratch.
Before installing the drivers, make sure there are no nvidia drivers already installed by doing the following:
$ sudo apt-get --purge remove nvidia-*
And reboot. Then download NVidia drivers from here and install them according to instructions.
First, install some AMD drivers that will be used by CUDA.
$ sudo apt-get install fglrx-updates
After installation, reboot the computer.
Next, stop the SSH X11 forwarding by modifying /etc/ssh/sshd_config:
$ sudo nano /etc/ssh/sshd_config
Find the following line:
and change it to:
After saving the changes, restart the ssh service by typing:
$ sudo service ssh restart
Now, stop the default X server by typing:
$ sudo service mdm stop
Now we can install CUDA. The latest supported version is 7.5 which can be downloaded from here. Select Linux > X86_64 > Ubuntu > 14.04 > runfile (local). Follow the instructions on the page to complete the installation.
After finishing the installation of CUDA, undo the change that you made to /etc/ssh/sshd_config, and restart the ssh server using
sudo service ssh restart. Also, start the X server again:
sudo service mdm start
Download cuDNN from here. Select a version which is compatible with CUDA. After downloading, do the following:
$ tar xvf <DOWNLOADED FILE NAME> $ cd cuda $ sudo cp */*.h /usr/local/cuda/include/ $ sudo cp */libcudnn* /usr/local/cuda/lib64/ $ sudo chmod a+r /usr/local/cuda/lib64/libcudnn*
To install for all users
$ sudo -i
then install package.
git clone in
~\repos if need.
To install only for user then add
--user at the end. E.g.:
$ python setup.py install --user
Here are some specific instructions:
$ pip install theano
[global] floatX = float32 device = gpuX
gpuX your assigned gpu, there will be random inspections. Grad students all share
$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.10.0rc0-cp27-none-linux_x86_64.whl $ pip install --ignore-installed --upgrade $TF_BINARY_URL
Note: right now
tensorflow is not working because we are using
cuDNN v5. Either wait for it to be compatible or downgrade
v4 when we really need to use tensorflow (don’t do it). Or try to compile/install
tensorflow from source (good luck with that).
$ pip install keras
See here to choose
$ git clone --recursive https://github.com/dmlc/xgboost $ cd xgboost; make -j4 $ cd python-package $ python setup.py install
$ conda install opencv