Leveraging the GPU to accelerate the Linux kernel

Powerful graphics cards are pretty affordable these days. Even though we rarely do high-end gaming on our daily machine we still have aย GeForce 9800 GT. That goes to waste on a machine used mainly to publish posts and write code for microcontrollers. But perhaps we can put the GPU to good use when it comes compile time. The KGPU package enlists your graphics card to help the kernel do some heavy lifting.

This won’t work for just any GPU. The technique uses CUDA, which is a parallel computing package for NVIDIA hardware. But don’t let lack of hardware keep you from checking it out. [Weibin Sun] is one of the researchers behind the technique. He posted a whitepaper (PDF) on the topic over at his website.

Add this to the growing list of non-graphic applications for today graphics hardware.

UPDATE: Looks like we won’t be trying this out after all. Your GPU must support CUDA 2.0 or higher. We found ours on this list and it’s only capable of CUDA 1.0.

[Thanks John]

GPU Processing and Password Cracking

Recently, research students at Georgia Tech released a report outlining the dangers that GPUs pose to the current state of password security. There are a number of ways to crack a password, all with their different pros and cons, but when it comes down to it, the limiting factor in all of these methods is processing complexity. The more operations that need to be run, the longer it takes, and the less useful each tool is for cracking passwords. In the past, most recommendations for password security revolved around making sure your password wasn’t something predictable, such as “password” or your birthday. With today’s (and tomorrows) GPUs, this may no longer be enough.

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