Bench Press

Some scary news if you’re an IT guy (although promising if, like us, you believe in the power of alternative processors), but basically it shows that the Playstation 3′s super-powered Cell processor really is useful for more than just Metal Gear Solid. 

Brilliant visual depiction of research described below

By using the computational power of a cluster of 200 PS3s, researchers were able to create a fake certificate allowing them to usurp certification authority from Verisign’s RapidSSL public encryption method. What that means is that the researcher’s were able to create their own certificates, meaning that they could fool any browser into believing whatever identity the researchers threw at them. Translated into real-world terms, it means that the researchers could have, had they wanted to, convinced your browser that they were your bank, your ISP, eBay, or potentially a legitimate Microsoft/Apple software update. 

Image of the "Playstation Lab" cluster which executed the hack.

The source of the hack comes from a weakness in using MD5, a popular hash-generating function which is supposed to turn large files into short 128-bit “passwords”. A 128-bit password may not seem like much (imagine converting a 200 page book into a short 200-letter sentence, you can’t recreate the book from that sentence), but the magic is that, like other cryptography methods, it is supposed to be incredibly difficult to create two files with the same MD5 “password” — a so-called “collision”. 

However, MD5 is not perfect, as a computationally intensive means of finding collisions was demonstrated in 2007, and while many certificate authorities had switched away from MD5, there were few who genuinely believed that the computational power was readily available to break it. And, while 200 Playstation 3′s is not super-easy to come by, given the profitability of such a scam, this recent exploit demonstrates that it no longer requires a massive multi-million dollar supercomputer to do the number-crunching needed (the researchers estimated that only $20,000 worth of computing power on Amazon’s Elastic Compute Cloud was needed to generate the fake certificate).

Thankfully, Verisign has confirmed that they are committed to phasing out MD5, and Microsoft and Mozilla have been fully briefed on the risk. Let us hope that is more than just empty promises.

(Image source: Playstation Lab cluster)

As the problems scientists solve become more and more complex, so do their demands for computational power. One approach to addressing this has been to build faster, more powerful computers, potentially with chips better suited to performing advanced calculations (like graphics cards or IBM’s Cell processor). But, this approach has serious limitations — mainly that it’s expensive to build and to maintain these supercomputers.

Some researchers, however, have turned to a radically different approach. Instead of building a bigger, better mousetrap to deal with more mice, the distributed computing approach takes the approach of placing many small, cheap mousetraps. The result is cheap “supercomputers” which are able to “pool” the computing power of many computers connected over a network.

This approach has been used by projects like Folding@Home and SETI@Home which are able to combine computing power from volunteers over the internet to do the number-crunching needed to simulate protein folding or scan deep space for extraterrestrial life. SETI@Home was the first such large-scale distributed computing platform. This platform, now the Berkeley Open Infrastructure for Network Computing (BOINC), is today used for many other distributed computing projects such as attempts to search for gravitational waves, do climate modeling, and simulate particle collisions in the Large Hadron Collider.

Folding@Home, a project started by the Pande group at Stanford to use distributed computing to study protein folding uses a similar approach, albeit with different underlying software (is it any wonder that a Stanford group doesn’t use Berkeley’s distributed computing platform?! ) . It has probably been the most successful distributed computing approach to date, and, as a testament to the power of distributed computing, has become known as the first computing system to break the petaFLOPS barrier – e.g. capable of one quadrillion floating point calculations per second! This has enabled the team to do protein-folding simulations on a scale of ~10 micro-seconds.

But, as impressive as the science achieved by distributed computing projects is, what impresses me the most is that projects like Folding@Home and SETI@Home have defined some brilliant new ways to do science:

• Use the internet – It’s a common theme on Bench Press, but with more and more people having faster and faster access to the internet, the potential for distributed computing becomes greater and greater. As Folding@Home demonstrated, such approaches can produce computing systems as powerful (or potentially more powerful) as leading supercomputer systems at a fraction of the cost.
• Mobilize the public – We’ve discussed ways for the scientific community to reach out to the public like using social media and creating interactive applications/tools for the public to use, but efforts like Folding@Home illustrate a way to not only reach out to the public but to get them vested in science. In a world where high school science teachers find it difficult to get teens interested in science, initiatives like Folding@Home have created a system where teams of individuals compete on who can contribute the most to the effort! Instead of simply hoping that the public will continue to fund and listen, why not borrow a page from the many existing cancer-walk-a-thons and make it easy for the public to get involved?
• Leverage new technology – It may not come as a surprise to our readers that a significant amount of the computational power at Folding@Home comes from graphics cards and Playstation 3’s. But, while many “mainstream” supercomputers ignored the new power afforded by these new chip types, Folding@Home developed software so that volunteers could quickly and easily use these powerful chips to boost their Folding@Home scores. The Folding@Home initiative also developed software to take advantage of innovations AMD and Intel included in their chips (new multi-core architectures and special instructions to speed up calculations). Is it any wonder, then, that Sony, NVIDIA, and AMD have all publically announced support for the initiative with their products?

I don’t pretend that every scientific problem is amenable to a distributed computing initiative, but to some extent, I believe that every scientific endeavor has something valuable to learn from the success of Folding@Home and SETI@Home and their brethren. To that end, I sincerely hope to see an open-source distributed computing architecture like BOINC but with:

• Support for new chip technologies – To provide greater value to the scientific effort, the architecture should support new chip technologies like Intel’s SSE extensions, SMP, or stream processing
• Client contribution tracking – To make it easier for volunteers to know how much they’ve contributed and/or have contests on how much they’ve contributed, a simple system to enable users/administrators to track the effort is needed
• Better security – Medical initiatives and volunteer privacy concerns demand that very fine and specialized security controls are necessary. Support for sophisticated encryption and authentication are a must.
• Linkage to social media – This probably seems extraneous, but since distributed computing efforts depend on motivated volunteers actively seeking out new volunteers, a successful architecture needs to make it easy for volunteers to share their progress with their friends whether it be via blog, or social network, or Twitter, or anything.
• Tie-in with new cloud computing systems – Along the theme of cutting costs, it is reasonable to assume that as offerings like Google’s App Engine and Amazon’s EC2 and technologies like MapReduce become better developed, we will see cash-strapped research groups using the power of “Clouds” to hold their computing power – after all, what is distributed/grid computing other than a specific variant of cloud computing (de-localized, pooled computing)? It’s probably necessary, then, for the new distributed computing architecture to more easily link with EC2 or MapReduce or App Engine.

Anyone else have any thoughts?

(Image Credit – picture of the internet) (Image Credit – Folding@Home computing power)

There was a time when video game consoles and graphics cards were “just for games.” In those days, game console chips and graphics cards were the domain of little boys, not grown men. Well, thank the stars those days are long gone!

Today, if someone were to tease a grown man for purchasing Sony’s Playstation 3, he could simply reply, “I beg your pardon. I am a grown man, not a little boy. I am clearly using the Playstation 3, not to play great games like Grand Theft Auto IV and Metal Gear Solid, but to use its TeraFLOPS (1 trillion floating point calculations per second) capacity to solve important and complex scientific problems.”

It almost sounds like a fantasy, but it’s not. The idea behind this is pretty basic. To make games and graphics run smoothly, video game console chips and graphics cards have to do a mind-boggling number of calculations much faster than a basic computer chip can. It “just so happens” that the supercomputers scientists and Wall Street analysts use to do simulations and research with also need to do those same types of calculations. Hence the idea of Stream Processing was born – why not use graphics card/game console chips for things which aren’t directly related to graphics or gaming?

Why not indeed? I can’t list all of the projects out there, but here’s just a snapshot of the scientific applications that people have been able to do with the Playstation 3’s unique chip, IBM’s Cell Broadband Engine, and graphics cards from NVIDIA and AMD:

• Researchers at the National Center for Atmospheric Research used NVIDIA’s CUDA stream processing platform to improve the speed of their weather forecasting models
• Astrophysicist Gaurav Khanna from UMass Dartmouth used 16 Playstation 3’s to simulate the collision of two black holes
• AMD researchers were able to demonstrate the use of AMD graphics cards to let a computer see in 3D and then map that image to an actual physical simulation
• The Los Alamos National Laboratories turned to IBM to design them a new supercomputer, but instead of just designing them with plain vanilla chips from Intel and AMD, they asked for a new breed of computer. Enter the Roadrunner, a computer which when fully operational will be capable of PetaFLOPS performance (1 quadrillion floating point calculations per second), and consists of ~7000 AMD Opteron chips coupled with ~13000 Cell processors
• The University of Illinois at Urbana-Champaign, by using 3 NVIDIA graphics processors, was able to help perform biochemical simulations at a submolecular level 100 times faster than 18 typical computer CPUs.

Technology – it’s good for more than just playing games.

Image Credit