Posts Tagged distributed

Folding@home to utilize your graphics processor

I thought about this briefly, myself, while in computer architecture optimization classes. As the GPU is basically a tailored CPU used to offload graphics processing from the main CPU, why can’t you offload more things onto it?’

And the answer is: you can. Folding@Home is a distributed computing project that is developed by Stanford University, and has been around awhile. While I don’t currently use it, I have in the past. I support the World Community Grid project, currently, because it gets me free gigs on Easynews, and it works with the Boinc client for my linux machines. But, Folding@Home always seemed to be the most efficient at what it does. No frills, no fancy screensavers, little overhead. It just folds and folds and folds protein.

Now, it can stake claim to unused GPU cycles on that roaring video card you have. And you only use a fraction of those while not going for that next rank in Battlefield 2. Desktop computing can even consider to have an idle 3d processor, for the most part.

Unfortunately, they only have this working on ATI cards. They couldn’t get it working on the Nvidia flavors. This leaves me out in the cold, at least for now. The chips are just a bit too specialized, and not in the “general” category of GPU’s anymore.

Andy Keane, general manager of visualization applications at Nvidia, said in response to the ATI/Stanford announcement that general processing graphics processing units (GPGPUs) so far have been “fundamentally flawed” in a sense that there has not been a lot of “commercial exploitation with GPUs as a processor.”

He mentioned that Nvidia wants to change this situation and considers the GPGPU market as “exciting” and something that “the company has been looking at for years.” He stated that he had no personal knowledge of the development of a Folding@Home client for the Nvidia platform, but stressed that the company has a “long-standing relationship with Stanford.”

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Distributed Eyeballing

There has been a wave of distributed computing projects over the years. The first big public one was SETI@Home, the search for extraterrestrial radio signals from intelligent beings. (Although, some may argue that that crown should be given to GIMPS, the search for ever larger Mersenne Primes). Sometimes associated with wacky UFO dreamers that call Art Bell nightly, and othertimes applauded for it’s novel approach to a huge issue: How to sort through infinitely long radios streams on infinitely many channels, to possibly find someone else out there.

Eventually, the concept started to catch on. Cancer research, AIDS research, protein folding, artificial intelligence, Riemann Zeta functions… you name it, there was some kind of distributed computing project for it.aerogel stardust track

Stardust@Home doesn’t use your computer to process data, it uses your eyes. It uses everyones eyes to scan a sheet of aerogel at microscopic levels to find interstellar dust.

On January 15, 2006, the Stardust spacecraft’s sample return capsule parachuted gently onto the Utah desert. Nestled within the capsule were precious particles collected during Stardust’s dramatic encounter with comet Wild 2 in January of 2004 and something else, even rarer and no less precious: tiny particles of interstellar dust that originate in distant stars, light-years away. They are the first such pristine particles ever collected in space, and scientists are eagerly waiting for their chance to “get their hands” on them.

Before they can be studied, though, these tiny interstellar grains will have to be found. This will not be easy. Unlike the thousand of particles of varying sizes collected from the comet, scientists estimate that Stardust collected only around 45 interstellar dust particles. They are tiny—only about a micron (a millionth of a meter) in size! These miniscule particles are embedded in an aerogel collector 1,000 square centimeters in size. To make things worse the collector plates are interspersed with flaws, cracks, and an uneven surface. All this makes the interstellar dust particles extremely difficult to locate.

If we were doing this project twenty years ago, we would have searched for the tracks through a high-magnification microscope. Because the view of the microscope is so small, we would have to move the microscope more than 1.6 million times to search the whole collector. In each field of view, you would focus up and down by hand to look for the tracks. This is so much work, that even starting twenty years ago, we would still be doing it today!

I’ve been waiting for this project to finally start, as it’s been delayed a few times over the last year. But it finally started last week, and I have given several goes to the image viewer. I can’t stare at the images for too long, but I can give it a few minutes a day. I like the direction that it takes us. I mean, the search for interstellar dust is neat and all, but what I really mean is the way it is taking distributed “computing” to another level.

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