Installing and configuring NVIDIA video card drivers

In this , we will embrace CUDA, the NVIDIA parallel computing architecture. The first step will be the installation of the NVIDIA developer display driver followed by the installation of the CUDA toolkit. This will provide us with a dramatic increase in computer performance with the power of the GPU, which will be used in scenarios such as password cracking.

The following requirements need to be fulfilled:

1.       An Internet connection is required to complete this recipe

2.       The preparation of the kernel headers is needed before starting this task, which is explained in the Preparing kernel headers recipe at the beginning of this chapter

3.       In order to accomplish the installation of the NVIDIA driver, the X session needs to be shut down

How to do it...

Let's begin the process of installing and configuring the NVIDIA video card driver:

1.        Download the NVIDIA developer display driver according to your CPU architecture:

cd /tmp/

wget http://developer.download.nvidia.com/compute/cuda/4_1/rel/driv ers/NVIDIA-Linux-x86_64-285.05.33.run

2. Install the driver:

chmod +x NVIDIA-Linux-x86_64-285.05.33.run

./NVIDIA-Linux-x86_64-285.05.33.run –kernel-source-path='/usr/src/linux'

3. Download the CUDA toolkit:

wget http://developer.download.nvidia.com/compute/cuda/4_1/rel/tool kit/cudatoolkit_4.1.28_linux_64_ubuntu11.04.run

4. Install the CUDA toolkit to /opt:

chmod +x cudatoolkit_4.1.28_linux_64_ubuntu11.04.run

./cudatoolkit_4.1.28_linux_64_ubuntu11.04.run

5. Configure the environment variables required for nvcc to work:

echo PATH=$PATH:/opt/cuda/bin >> ~/.bashrc

echo LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/cuda/lib >> ~/.bashrc

echo export PATH >> ~/.bashrc

echo export LD_LIBRARY_PATH >> ~/.bashrc

6. Run the following command to make the variables take effect:

source ~/.bashrc

ldconfig

7. Install Pyrit dependencies:

apt-get install libssl-dev python-dev python-scapy

8. Download and install the GPU powered tool, Pyrit:

svn co http://pyrit.googlecode.com/svn/trunk/ pyrit_src

cd pyrit_src/pyrit

python setup.py build

python setup.py install

9. Finally, add the NVIDIA GPU module to Pyrit:

cd /tmp/pyrit_src/cpyrit_cuda

python setup.py build

python setup.py install