Sunday, December 25, 2011

HOWTO : BackTrack 5 R1 on Intel X79 Express chipset and nVidia display card

Hardware

CPU : Intel i7-3930K (Socket 2011, 12 cores with HT)
Display card : 2 x nVidia GeForce GTX 590 (1024 CUDA cores per card)

Installation of BackTrack 5 R1

BackTrack 5 R1 can be boot up on Intel X79 Express chipset motherboard with 2 nVidia GeForce GTX 590 display cards. However, "nomodeset" should be applied to the boot option by pressing "tab" on the boot menu.

Install the BackTrack 5 R1 as usual. When it is required to reboot, do not remove the BackTrack 5 R1 CD. Boot up the CD accordingly. After the BackTrack 5 R1 is booted up, mount the hard drive and add "nomodeset" to boot option of the grub.cfg at /boot/grub.

After that, reboot the system and remove the CD. The system will be boot into BackTrack 5 R1 without problem.

If the kernel is upgraded, you should rebuild the kernel headers by the following steps :

prepare-kernel-sources
cd /usr/src/linux
cp -rf include/generated/* include/linux/


Installation of nVidia display driver

Go to nVidia Deleloper Zone CUDA Toolkit 4.0 to download the following. Do not enter to X11 by issuing "startx"; otherwise, the installation will be failed.

(1) Download "Developer Drivers for Linux (270.41.19)" for the nVidia Driver.

32-bit :
wget http://developer.download.nvidia.com/compute/cuda/4_0/drivers/devdriver_4.0_linux_32_270.41.19.run

64-bit :
wget http://developer.download.nvidia.com/compute/cuda/4_0/drivers/devdriver_4.0_linux_64_270.41.19.run

chmod +x devdriver_4.0_linux_xx_270.41.19.run
./devdriver_4.0_linux_xx_270.41.19.run


(2) Download "CUDA Toolkit for Ubuntu Linux 10.10" for the CUDA Toolkit.

32-bit :
wget http://www.nvidia.com/object/thankyou.html?url=/compute/cuda/4_0/toolkit/cudatoolkit_4.0.17_linux_32_ubuntu10.10.run

64-bit :
wget http://www.nvidia.com/object/thankyou.html?url=/compute/cuda/4_0/toolkit/cudatoolkit_4.0.17_linux_64_ubuntu10.10.run

chmod +x cudatoolkit_4.0.17_linux_xx_ubuntu10.10.run
./cudatoolkit_4.0.17_linux_xx_ubuntu10.10.run


(3) Download "GPU Computing SDK" for the nVidia SDK.

wget http://developer.download.nvidia.com/compute/cuda/4_0/sdk/gpucomputingsdk_4.0.17_linux.run

chmod +x gpucomputingsdk_4.0.17_linux.run
./gpucomputingsdk_4.0.17_linux.run


nano /root/.bashrc

Append the following :

export PATH=$PATH:/usr/local/cuda/bin
LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib:/usr/local/cuda/lib64


After that, reboot the system to make the nVidia driver effect.

Installation of pyrit

Go to the official site of pyrit.

http://code.google.com/p/pyrit/downloads/list

Download pyrit and cpyrit-cuda (the current version is 0.4.0 at the time of this writing).

tar -xzvf pyrit-0.4.0.tar.gz
cd pyrit-0.4.0
python setup.py build
python setup.py install


tar -xzvf cpyrit-cuda-0.4.0.tar.gz
cd cpyrit-cuda-0.4.0
python setup.py build
python setup.py install


To test if the installation is correct or not.

pyrit list_cores
pyrit benchmark
pyrit benchmark_long


That's all! See you.

Before water cooling



After water cooling