backtrack-4-cuda-guide.pdf

BackTrack 4 CUDA Guide

Written by

Pureh@te

Table of Contents

What is CUDA? ................................................................................................................................................................. 3

Supported GPUs ................................................................................................................................................................ 3

Why do I care about CUDA?.............................................................................................................................................. 3

Where can I get this CUDA thing? ..................................................................................................................................... 3

What is CUDA not? ........................................................................................................................................................... 4

Getting started.................................................................................................................................................................... 4

Nvidia-drivers: ............................................................................................................................................................. 4

Overclocking: ............................................................................................................................................................... 5

Installing the CUDA toolkit and SDK : ......................................................................................................................... 8

CUDA Tools.................................................................................................................................................................... 12

CUDA-multiforcer:..................................................................................................................................................... 12

Pyrit ........................................................................................................................................................................... 14

What is pyrit?........................................................................................................................................................ 14

Up and running with pyrit...................................................................................................................................... 14

Making sure Pyrit is working:................................................................................................................................ 15

Passthrough Mode: ................................................................................................................................................ 16

Passthrough with Crunch: ...................................................................................................................................... 17

Server / Client Mode: ............................................................................................................................................ 21

Building aircrack-ng with CUDA support: .................................................................................................................. 23

Cuda Debugger:.......................................................................................................................................................... 24

Useful Links: ................................................................................................................................................................... 25

Special Thanks:................................................................................................................................................................ 25

What is CUDA?

CUDA (an acronym for Compute Unified Device Architecture) is a parallel computing architecture

developed by NVIDIA. CUDA lets programmers utilize a dedicated driver written using C language

subroutines to offload data processing to the graphics processing hardware found on Nvidia's late-

model GeForce graphics hardware. The software lets programmers use the cards to process data

other than just graphics, without having to learn OpenGL or how to talk with the card specifically.

Since CUDA tools first emerged in late 2006, Nvidia's seen them used in everything from consumer

software to industrial products, and the applications are limitless.

Supported GPUs

A complete list of supported GPU's can be found at the following link:

http://en.wikipedia.org/wiki/CUDA#Supported_GPUs

Why do I care about CUDA?

Hardware acceleration of password recovery is possible with CUDA enabled applications. Many of

these applications are already available and there are many more to come. The support of NVIDIA

graphic accelerators increases the recovery speed by an average of 10 to 15 times faster than was

previously possible.

Where can I get this CUDA thing?

Backtrack 4 pre final comes fully ready to execute and build CUDA powered applications. I will

review some of the major points involved in setting up the environment and running some of the

application.

What is CUDA not?

CUDA is not a magic bullet that will suddenly make all software on an Nvidia-equipped PC run

dramatically faster, in other words -- the programmer needs to figure out where the program can be

optimized to process data in parallel. But within that context, programming support for CUDA can

make a big difference.

Getting started

N vidia-drivers:

The first thing we need to do is get the nvidia drivers installed. This is done easily with Backtracks

package manger apt-get. Installing the nvidia drivers is best done while the X server is not running.

The X server can be stopped by pressing ctrl – alt -backspace.

Once you get the drivers installed, a new xorg-config should be generated for you and then you can

“startx” and return to the kde desktop environment.

In the event the auto xorg.conf does not work, nvidia provides a utility which may be able to help.

To invoke it simply type “nvidia-xconfig” into a terminal and it will try to generate a new xorg

config for you.

If you have multiple monitors you may need to use the nvidia-settings tool to configure them. In

order to use the settings tool, either launch it from the KDE menu or run the command “nvidia-

settings” in a terminal. The actual configuration is beyond the scope of this document however its

fairly easy to understand.

Overclocking:

There are two ways to overclock your video card in Linux. The first way is to use the nvidia-

settings tool which comes with the nvidia-driver. In order to do this you need to edit your xorg.conf

in order to unlock the option.

nano /etc/X11/xorg.conf

and find the section that looks like this:

Section "Device"

Identifier "Videocard1"

Driver "nvidia"

VendorName "NVIDIA Corporation"

BoardName "GeForce 8800 GT"

BusID "PCI:3:0:0"

Screen 1

Option "AddARGBGLXVisuals" "true"

Option "Coolbits" "1"

Option "RenderAccel" "true"

EndSection

Add the coolbits option and then restart X and open nvidia-settings and you should have a

overclock option like this:

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