tailieunhanh - BackTrack 4 CUDA Guide

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 latemodel 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 | BackTrack 4 CUDA Guide Written by Pureh@te 1 Table of Contents What is CUDA .3 Supported Why do I care about CUDA .3 Where can I get this CUDA thing .3 What is CUDA not .4 Getting Nvidia-drivers .4 Overclocking .5 Installing the CUDA toolkit and SDK .8 CUDA CUDA-multiforcer .12 What is pyrit .14 Up and running with 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 2 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 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.

• Cơ sở dữ liệu
• Nvidia driver
• CUDA
• CUDA Tools
• CUDA multiforcer
• Cuda Debugger
• Passthrough Mode