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U.S. institution recaptures title with 17.59 petaflop showing

NVIDIA Corp. (NVDA) is bringing out the big guns in the GPU market, pushing special Kepler "accelerator" hardware -- the big brother to NVIDIA's market-leading consumer gaming hardware.  Targeted at large supercomputer deployments, the Tesla K20X accelerator offers 3.95 teraflops of peak floating point precision performance and 1.17 teraflops of peak double performance.

To put that in context, a top-of-the-line server CPU -- the Westmere-EX 12-core, 2.4 GHz Xeon E7-8870 -- gets approximately 384 gigaflops of peak double performance [source].  With an average power performance of around 90 watts per core [source] when loaded, the Intel chip musters around 355 Megaflops per watt.  By contrast, the NVIDIA card gets about 2,142.77 Megaflops per watt. In other words, it's not only more powerful in terms of pure number crunching; it's also more efficient.

Of course, that comparison is slightly misleading; there are significant differences between GPU-accelerated multi-threaded computing and CPU multi-core computing in terms of memory resources and data transfer.
Tesla K20X
The world's most powerful supercomputer is now driven by NVIDIA's Tesla K20X GPUs.

But the numbers do start to give you an idea of why so many data centers are jumping on the GPU train.  NVIDIA announced on Monday that the completed "Titan" supercomputer at Oak Ridge National Laboratory in Oak Ridge, Tenn. just earned a "number one" ranking in the Top500 list of the world's most powerful supercomputers.

Powered by 18,688 NVIDIA Tesla cards, the installation posted a LINPACK score of 17.59 petaflops.  

Titan shows NVIDIA's arch-nemesis CPU/GPU-maker Advanced Micro Devices, Inc. (AMD) some love as well, utilizing its Opteron 6274 (Bulldozer) 16-core chips.  Paired with 710 terabytes of memory, the machine is capable of performing 1,000 quadrillion calculations per second using 20 megawatts of electricity or less.

Titan supercomputer
Titan unseats reigning champion Sequoia, a more traditional CPU-driven design from IBM.

Dr. Thomas Schulthess, professor of computational physics at ETH Zurich and director of the Swiss National Supercomputing Center cheers the record-setter, remarking, "We are taking advantage of NVIDIA GPU architectures to significantly accelerate simulations in such diverse areas as climate and meteorology, seismology, astrophysics, fluid mechanics, materials science, and molecular biophysics.  The K20 family of accelerators represents a leap forward in computing compared to NVIDIA's prior Fermi architecture, enhancing productivity and enabling us potentially to achieve new insights that previously were impossible."

The previous record holder was Lawrence Livermore National Laboratory's Sequoia system a Blue Gene supercomputer from International Business Machines, Inc. (IBM).  Sequoia is a more traditional CPU-based design, which uses PowerPC A2 processor chips.


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By Ammohunt on 11/13/2012 1:42:03 PM , Rating: 2
We are back to room sized computers...

RE: Interesting
By siconik on 11/13/2012 2:33:00 PM , Rating: 2
Back? Why, did performance-leading supercomputers deviate from "room-sized" form factor any point?

RE: Interesting
By Camikazi on 11/13/2012 4:03:46 PM , Rating: 2
Supercomputers have never stopped being room sized, in fact they went from room sized to apartment sized.

RE: Interesting
By inperfectdarkness on 11/14/2012 2:57:18 AM , Rating: 2
It's never changed. Peak PC performance will always be from something the size of a small airplane hangar. The "shrinking sizes" of which you are thinking are from PC's who have performance equal to YESTERDAY'S supercomputers. In 1993, 143.4 GFLOPS was the record. Back then it took a room. Today that's a home computer. Size is simply a function of how much power you can cram into it--relative to the year of manufacture.

RE: Interesting
By elderwilson on 11/14/2012 8:27:06 AM , Rating: 2
So if 1993's supercomputer is roughly equivalent to a top end PC today, when can we expect to see 2012 supercomputer performance in a consumer form? The easy answer would be about 2032, but I know someone has analyzed the data and could give a much better forecast.

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