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The Fastest Science Machine In The World


Oak Ridge National Labs has deployed what should be the world's fastest supercomputer when the world's petaflops are tabulated next month, and it is dedicated to open science.





With the release of the next TOP500 ranking of the world's fastest supercomputers just weeks away, Oak Ridge National Laboratory (ORNL) has this week officially deployed Titan, a 20-petaflop machine. Titan is expected to edge out Sequoia, another Department of Energy machine housed at Lawrence Livermore National Labs, putting the U.S. confidently back atop the supercomputing pyramid (Sequoia is expected to hold the number-two spot) after spending the last few years often chasing China and Japan.

But beyond bragging rights, Titan is something more. It will hands-down be the fastest open science machine in the world, granting time to scientists in industry, academia, and government labs around the country who need huge computing capabilities to make sense of complex data sets in six core areas: climate change, astrophysics, materials science, biofuels, combustion, and nuclear energy systems. And critically, it incorporates graphics processing units (GPUs) alongside the conventional central processing unit (CPU) cores normally deployed in supercomputers of this kind. This successful marriage of CPUs and GPUs could have far-reaching implications for the future of supercomputing as scientists strive to develop a next-generation exascale science machine.

"We bet the farm on this hybrid computing environment and we succeeded.""Titan will be the biggest and fastest open science computer today," says Steve Scott, chief technology officer for Tesla, the business unit of NVIDIA responsible for supplying Titan's GPUs. "It may or may not outpace Sequoia. It's nice to have those titles, but it's not as important as the science that's being done on the machine."

To the collaboration that developed Titan, whether or not its computer clocks in faster than the reigning champ over at Lawrence Livermore is an afterthought. Sequoia, an IBM BlueGene/Q system, is designed to run classified research for the DOE and thus will soon go off the radar, back behind the curtain of state secrecy where the average researcher will be hard pressed to gain access to it. Titan, on the other hand, is designed with open research in mind. And it's already ready to compute at a level the research science community has never before seen.


Titan is capable of producing 20,000 trillion calculations per second. To give you an idea of how far and how fast this computational capability has traveled, consider that back in 2009 ORNL was also home to the world's fastest supercomputer, named Jaguar (Titan is actually an upgrade of Jaguar rather than a from-scratch system, though Titan's architecture is very different). Jaguar was a 2.3-petaflops system ("flops" stands for floating-point operations per second and is the measurement of supercomputing performance) when it topped the world's list of fastest computers. In just three years, Titan has eclipsed Jaguar by ten times.

That leap forward was enabled largely by rethinking the way ORNL builds supercomputers. One could feasibly enhance computing capability by ten times by building a computer ten times larger with ten times more CPUs, but doing so would be impractical on many levels. Aside from the hardware challenges inherent in such a large machine, the energy needs of the 2.3-petaflop Jaguar were equivalent to that of 7,000 American homes. A 20-petaflop Jaguar would require something like 60 megawatts, or 60,000 homes' worth of energy to function. To get Titan to where it is now without building a massive energy suck took lots of collaboration, an increased reliance on a new kind of hardware regime, and a pretty serious dose of moxie.


"In 2009, we invented hybrid multi-core before we even had a word for it," says Jeffrey Nichols. "From there we made a three-year leap of faith that has paid off tremendously in a 10-times leap in performance, a five-times leap in efficiency."



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