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Supercomputer comes with new Nvidia 'Fermi' chip, ORNL and NVIDIA

The Oak Ridge's supercomputer which is expected to perform 10 times more powerful than today's fastest supercomputer used to purse research in energy and climate change, on getting towards it Oak Ridge National Laboratory (ORNL) announced plans for a new supercomputer that will use NVIDIA®’s next generation CUDA™ GPU architecture, codenamed “Fermi.

The architecture would use both graphics processing units (GPUs) from Nvida and central processing units (CPUs); plan announced by Oak Ridge National Laboratory (ORNL) that this super computer will come with Nvidia's next-generation GPU architecture, codenamed "Fermi."

The Fermi chip integrates three billion transistors, about three times the number of transistors in Nvidia's most powerful graphics chip now on the market. In the future, the chip will also find its way into Nvidia's GeForce product line for PCs, stated Oak Ridge and Nvidia's in the announcement.

“Fermi” would enable substantial scientific breakthroughs that would be impossible without the new technology, “This would be the first co-processing architecture that Oak Ridge has deployed for open science, and we are extremely excited about the opportunities it creates to solve huge scientific challenges,” Nichols said. “With the help of NVIDIA technology, Oak Ridge proposes to create a computing platform that will deliver exascale computing within ten years.” Told Jeff Nichols, ORNL associate lab director for Computing and Computational Sciences, joined NVIDIA co-founder and CEO Jen-Hsun Huang on stage during his keynote at NVIDIA’s GPU Technology Conference.

ORNL also announced it will be creating the Hybrid Multicore Consortium. The goals of this consortium are to work with the developers of major scientific codes to prepare those applications to run on the next generation of supercomputers built using GPUs.
“The first two generations of the CUDA GPU architecture enabled NVIDIA to make real in-roads into the scientific computing space, delivering dramatic performance increases across a broad spectrum of applications,” said Bill Dally, chief scientist at NVIDIA.

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