t e c h i e - t a l k s ::: technology at its best

Moscow (Russia) - It may not be the most popular thing to consider, but high-end graphics cards contain a very powerful internal computing engine, called the GPU. This massively parallel device can attack a problem in parallel, rather than serial as most CPUs are required to process data. This means it can compute many hundreds of simultaneous calculations. This is actually how 3D graphics cards get their high-speed gaming abilities. Still, a new use has been found for this robust computing engine: password cracking.

Elcomsoft, based out of Moscow, has filed a patent for using a GPU to crack passwords. The company has demonstrated that by using a high-end NVIDIA-based GeForce 8800 Ultra (about $620), the company was able to increase its password cracking prowess by a factor of 25. Even using $150 GPU cards greatly decreased comput time. This means that whereas it might’ve taken 25 days previously to brute-force crack a password, the exact same machine with only a single 8800 Ultra could do it in a day. This trend allows for passwords which could’ve taken two years previously to now be broken in only two weeks with only two cards running at 100%. And one week with four on two machines.

Today’s high-end graphics cards carry with them about 500 Gigaflops of computing power per GPU. Modern day link technology, like NVIDIA’s SLI or ATI’s CrossFire, allow for two or three of these cards to be linked together to increase computing capacity to over 1.5 teraflops. To put that number in perspective, the entire theoretical computational capacity of National Center for Supercomputing Applications (NCSA) in Urbana, Illinois, is 163 teraflops, though the actual real-world number is only about 96 teraflops. Their most powerful machine is capable of only 60 teraflops. To put this in perspective, for a cash outlay of less than $70,000, a person could equip themselves with enough high-end graphics cards to compute at a sustained rate in excess of 90 teraflops. Of course this would only be on certain tasks, but it is possible.

The technology which drives the massively parallel computing engine inside of a GPU has been used for low-level 3D and gaming engines for some time. Popular models like OpenGL and DirectX actually take the user-programmable code and convert it to the GPU’s internal computing language. These outward standards allow the peculiarities of the graphics engine to be hidden from programmers, thereby making a once-programmed 3D game or application run on many different graphics card platforms.

The same kind of technology is now being added to math libraries. These math libraries extend the base abilities of common programming languages like C or C++. They allow a user to create a custom program which can utilize the massively parallel computing abilities of a graphics card, but in a way that is not overtly complex to code nor specific to the model of the machine. One such example is NVIDIA’s CUDA software development platform, another is ATI’s Close-To-Metal, or CTM. Both of these allow a programmer to use the compute engines of the GPU cards in the system to carry out regular data processing, and not just graphics manipulation.

Some concerns will likely be raised about the strength of current cipher keys. Whereas with previous computational abilities it would’ve taken an entity like the NCSA a few hours or days to crack a heavily encrypted password, with regular machines taking years, now basically anybody with a half dozen high-end graphics cards can basically do the same thing in close to the same time. In short, what only governments used to only be able to do, regular people are now able to do.

Source: tgdaily.com